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overflow: hidden; text-overflow: ellipsis; -webkit-line-clamp: 3; -webkit-box-orient: vertical; }</style><div class="col-xs-12 clearfix"><div class="u-floatLeft"><h1 class="PageHeader-title u-m0x u-fs30">Educational Data Mining</h1><div class="u-tcGrayDark">19,142 Followers</div><div class="u-tcGrayDark u-mt2x">Recent papers in <b>Educational Data Mining</b></div></div></div></div></div></div><div class="TabbedNavigation"><div class="container"><div class="row"><div class="col-xs-12 clearfix"><ul class="nav u-m0x u-p0x list-inline u-displayFlex"><li class="active"><a href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Top Papers</a></li><li><a href="https://www.academia.edu/Documents/in/Educational_Data_Mining/MostCited">Most Cited Papers</a></li><li><a href="https://www.academia.edu/Documents/in/Educational_Data_Mining/MostDownloaded">Most Downloaded Papers</a></li><li><a href="https://www.academia.edu/Documents/in/Educational_Data_Mining/MostRecent">Newest Papers</a></li><li><a class="" href="https://www.academia.edu/People/Educational_Data_Mining">People</a></li></ul></div><style type="text/css">ul.nav{flex-direction:row}@media(max-width: 567px){ul.nav{flex-direction:column}.TabbedNavigation li{max-width:100%}.TabbedNavigation li.active{background-color:var(--background-grey, #dddde2)}.TabbedNavigation li.active:before,.TabbedNavigation li.active:after{display:none}}</style></div></div></div><div class="container"><div class="row"><div class="col-xs-12"><div class="u-displayFlex"><div class="u-flexGrow1"><div class="works"><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_51551287" data-work_id="51551287" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/51551287/Call_for_Papers_3_rd_International_Conference_on_Data_Mining_and_Machine_Learning_DMML_2022_">Call for Papers - 3 rd International Conference on Data Mining & Machine Learning (DMML 2022)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">3 rd International Conference on Data Mining & Machine Learning (DMML 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Mining and Machine... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_51551287" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">3<br />rd International Conference on Data Mining & Machine Learning (DMML 2022) will act as<br />a major forum for the presentation of innovative ideas, approaches, developments, and research<br />projects in the areas of Data Mining and Machine Learning. It will also serve to facilitate the<br />exchange of information between researchers and industry professionals to discuss the latest issues<br />and advancement in the area of Big Data and Machine Learning.<br />Authors are solicited to contribute to the conference by submitting articles that illustrate research<br />results, projects, surveying works and industrial experiences that describe significant advances in<br />Data Mining and Machine Learning.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/51551287" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e0fa074f7104d3d4f965e8f52fd84fc4" rel="nofollow" data-download="{"attachment_id":83189779,"asset_id":51551287,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/83189779/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26196263" href="https://independent.academia.edu/journalijwest">International Journal of Web & Semantic Technology (IJWesT)</a><script data-card-contents-for-user="26196263" type="text/json">{"id":26196263,"first_name":"International Journal of Web \u0026 Semantic Technology","last_name":"(IJWesT)","domain_name":"independent","page_name":"journalijwest","display_name":"International Journal of Web \u0026 Semantic Technology (IJWesT)","profile_url":"https://independent.academia.edu/journalijwest?f_ri=23995","photo":"https://0.academia-photos.com/26196263/7208853/161117496/s65_international_journal_of_web_semantic_technology._ijwest_.jpg"}</script></span></span></li><li class="js-paper-rank-work_51551287 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="51551287"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 51551287, container: ".js-paper-rank-work_51551287", }); 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It will also serve to facilitate the\nexchange of information between researchers and industry professionals to discuss the latest issues\nand advancement in the area of Big Data and Machine Learning.\nAuthors are solicited to contribute to the conference by submitting articles that illustrate research\nresults, projects, surveying works and industrial experiences that describe significant advances in\nData Mining and Machine Learning.","downloadable_attachments":[{"id":83189779,"asset_id":51551287,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26196263,"first_name":"International Journal of Web \u0026 Semantic Technology","last_name":"(IJWesT)","domain_name":"independent","page_name":"journalijwest","display_name":"International Journal of Web \u0026 Semantic Technology (IJWesT)","profile_url":"https://independent.academia.edu/journalijwest?f_ri=23995","photo":"https://0.academia-photos.com/26196263/7208853/161117496/s65_international_journal_of_web_semantic_technology._ijwest_.jpg"}],"research_interests":[{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=23995","nofollow":false},{"id":442,"name":"Parallel Computing","url":"https://www.academia.edu/Documents/in/Parallel_Computing?f_ri=23995","nofollow":false},{"id":447,"name":"Scientific Visualization","url":"https://www.academia.edu/Documents/in/Scientific_Visualization?f_ri=23995","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":4278,"name":"Web Mining","url":"https://www.academia.edu/Documents/in/Web_Mining?f_ri=23995"},{"id":8270,"name":"Forecasting","url":"https://www.academia.edu/Documents/in/Forecasting?f_ri=23995"},{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=23995"},{"id":12417,"name":"Multimedia Learning","url":"https://www.academia.edu/Documents/in/Multimedia_Learning?f_ri=23995"},{"id":15426,"name":"Spatial Data Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Spatial_Data_Mining_Data_Mining_?f_ri=23995"},{"id":17613,"name":"Forest biometrics","url":"https://www.academia.edu/Documents/in/Forest_biometrics?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":27360,"name":"Databases","url":"https://www.academia.edu/Documents/in/Databases?f_ri=23995"},{"id":39682,"name":"Graph Data Mining","url":"https://www.academia.edu/Documents/in/Graph_Data_Mining?f_ri=23995"},{"id":80870,"name":"Parallel \u0026 Distributed Computing","url":"https://www.academia.edu/Documents/in/Parallel_and_Distributed_Computing?f_ri=23995"},{"id":81182,"name":"Deep Learning","url":"https://www.academia.edu/Documents/in/Deep_Learning?f_ri=23995"},{"id":84990,"name":"Clustering","url":"https://www.academia.edu/Documents/in/Clustering?f_ri=23995"},{"id":115676,"name":"Cyber Security","url":"https://www.academia.edu/Documents/in/Cyber_Security?f_ri=23995"},{"id":565185,"name":"Video to Text","url":"https://www.academia.edu/Documents/in/Video_to_Text?f_ri=23995"},{"id":1916214,"name":"Evaluating of Credit Demands","url":"https://www.academia.edu/Documents/in/Evaluating_of_Credit_Demands?f_ri=23995"},{"id":2923288,"name":"Pre-Processing Techniques","url":"https://www.academia.edu/Documents/in/Pre-Processing_Techniques?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_24310549" data-work_id="24310549" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/24310549/Use_of_Educational_Apps_in_Todays_Classroom">Use of Educational Apps in Todays Classroom</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In today’s world, various tools and technologies have been used in learning. The rapid and constant pace of change in technology increases opportunity for students. The opportunities include greater access to rich, multimedia content, the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_24310549" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In today’s world, various tools and technologies have been used in learning. The rapid and constant pace of change in technology increases opportunity for students. The opportunities include greater access to rich, multimedia content, the widespread availability of mobile computing devices, the expanding role of social networking tools for learning and professional development, and the growing interest in the power of digital games for more personalized learning. According to the National School Boards Association, students who are exposed to a high volume of technology perform as well as expected on standardized test [1]. Various Multi-National Companies like Google and Apple are introducing new Educational Apps which combines interactive technology with educational materials that has been proven to help accelerate learning and promote more innovative methods of retention than a simple textbook and a set of cue cards could ever do. In this paper, we would like to emphasize the importance of Educational Apps in class room teaching. Specific topics addressed include: (a) Various Educational Apps and its use inside the classroom (b) Universities promoting the use of Educational Apps (c) Challenges and Disadvantages in using Educational Apps (d) Directions for future research.<br />Keywords— Educational Technology Tools, Technology and learning, Research designs and trends, Impact of technology on learning, Educational Apps, Google Apps, IPAD App.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/24310549" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="19e530b2448bc935cdb9e335f735025c" rel="nofollow" data-download="{"attachment_id":44647622,"asset_id":24310549,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/44647622/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8659111" href="https://bluecrestcollege.academia.edu/SujithJayaprakash">Sujith Jayaprakash</a><script data-card-contents-for-user="8659111" type="text/json">{"id":8659111,"first_name":"Sujith","last_name":"Jayaprakash","domain_name":"bluecrestcollege","page_name":"SujithJayaprakash","display_name":"Sujith Jayaprakash","profile_url":"https://bluecrestcollege.academia.edu/SujithJayaprakash?f_ri=23995","photo":"https://0.academia-photos.com/8659111/2904056/13784865/s65_sujith.jayaprakash.jpg"}</script></span></span></li><li class="js-paper-rank-work_24310549 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="24310549"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 24310549, container: ".js-paper-rank-work_24310549", }); 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$(".js-view-count[data-work-id=24310549]").text(description); $(".js-view-count-work_24310549").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_24310549").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="24310549"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4278" href="https://www.academia.edu/Documents/in/Web_Mining">Web Mining</a>, <script data-card-contents-for-ri="4278" type="text/json">{"id":4278,"name":"Web Mining","url":"https://www.academia.edu/Documents/in/Web_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="26860" href="https://www.academia.edu/Documents/in/Cloud_Computing">Cloud Computing</a><script data-card-contents-for-ri="26860" type="text/json">{"id":26860,"name":"Cloud Computing","url":"https://www.academia.edu/Documents/in/Cloud_Computing?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=24310549]'), work: {"id":24310549,"title":"Use of Educational Apps in Todays Classroom","created_at":"2016-04-11T23:26:09.060-07:00","url":"https://www.academia.edu/24310549/Use_of_Educational_Apps_in_Todays_Classroom?f_ri=23995","dom_id":"work_24310549","summary":"In today’s world, various tools and technologies have been used in learning. The rapid and constant pace of change in technology increases opportunity for students. The opportunities include greater access to rich, multimedia content, the widespread availability of mobile computing devices, the expanding role of social networking tools for learning and professional development, and the growing interest in the power of digital games for more personalized learning. According to the National School Boards Association, students who are exposed to a high volume of technology perform as well as expected on standardized test [1]. Various Multi-National Companies like Google and Apple are introducing new Educational Apps which combines interactive technology with educational materials that has been proven to help accelerate learning and promote more innovative methods of retention than a simple textbook and a set of cue cards could ever do. In this paper, we would like to emphasize the importance of Educational Apps in class room teaching. Specific topics addressed include: (a) Various Educational Apps and its use inside the classroom (b) Universities promoting the use of Educational Apps (c) Challenges and Disadvantages in using Educational Apps (d) Directions for future research.\nKeywords— Educational Technology Tools, Technology and learning, Research designs and trends, Impact of technology on learning, Educational Apps, Google Apps, IPAD App.\n","downloadable_attachments":[{"id":44647622,"asset_id":24310549,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":8659111,"first_name":"Sujith","last_name":"Jayaprakash","domain_name":"bluecrestcollege","page_name":"SujithJayaprakash","display_name":"Sujith Jayaprakash","profile_url":"https://bluecrestcollege.academia.edu/SujithJayaprakash?f_ri=23995","photo":"https://0.academia-photos.com/8659111/2904056/13784865/s65_sujith.jayaprakash.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":4278,"name":"Web Mining","url":"https://www.academia.edu/Documents/in/Web_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":26860,"name":"Cloud Computing","url":"https://www.academia.edu/Documents/in/Cloud_Computing?f_ri=23995","nofollow":false},{"id":194584,"name":"Google Apps","url":"https://www.academia.edu/Documents/in/Google_Apps?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_59225077" data-work_id="59225077" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/59225077/The_Use_of_Data_Mining_to_Model_Personalized_Learning_Management_System">The Use of Data Mining to Model Personalized Learning Management System</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Licensure Examination performance is a growing concern of most of the educational institution because it is one of the determinants of quality education and validates high quality instruction. Educational institution is focused on... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_59225077" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Licensure Examination performance is a growing concern of most of the educational institution because it is one of the determinants of quality education and validates high quality instruction. Educational institution is focused on monitoring and improving the Licensure Examination performance particularly in Teacher Education Institution (TEI). The study intends to offer a possible solution to most TEIs apprehensions regarding LET performance by providing the students of Teacher Education a student support service in the form of a personalized Learning Management System with performance prediction and recommendation capability. This can be developed through drawing data model using several data mining techniques and tools. Previous literature suggested using data mining to classify students, predict student performance, improve student retention, enhanced student achievement and assess complex students? behavior to name a few. This research project will provide the groundwork for th...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/59225077" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a99887fa68cfc3ef3a14a98df5b8f74d" rel="nofollow" data-download="{"attachment_id":73257497,"asset_id":59225077,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/73257497/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="40135201" href="https://lspu.academia.edu/MVillarica">Mia Villarica</a><script data-card-contents-for-user="40135201" type="text/json">{"id":40135201,"first_name":"Mia","last_name":"Villarica","domain_name":"lspu","page_name":"MVillarica","display_name":"Mia Villarica","profile_url":"https://lspu.academia.edu/MVillarica?f_ri=23995","photo":"https://0.academia-photos.com/40135201/12148822/54104924/s65_mia.villarica.jpg"}</script></span></span></li><li class="js-paper-rank-work_59225077 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="59225077"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 59225077, container: ".js-paper-rank-work_59225077", }); });</script></li><li class="js-percentile-work_59225077 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 59225077; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_59225077"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_59225077 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="59225077"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 59225077; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=59225077]").text(description); $(".js-view-count-work_59225077").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_59225077").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="59225077"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="19870" href="https://www.academia.edu/Documents/in/Research">Research</a>, <script data-card-contents-for-ri="19870" type="text/json">{"id":19870,"name":"Research","url":"https://www.academia.edu/Documents/in/Research?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="555965" href="https://www.academia.edu/Documents/in/Advanced">Advanced</a><script data-card-contents-for-ri="555965" type="text/json">{"id":555965,"name":"Advanced","url":"https://www.academia.edu/Documents/in/Advanced?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=59225077]'), work: {"id":59225077,"title":"The Use of Data Mining to Model Personalized Learning Management System","created_at":"2021-10-20T23:29:11.902-07:00","url":"https://www.academia.edu/59225077/The_Use_of_Data_Mining_to_Model_Personalized_Learning_Management_System?f_ri=23995","dom_id":"work_59225077","summary":"Licensure Examination performance is a growing concern of most of the educational institution because it is one of the determinants of quality education and validates high quality instruction. Educational institution is focused on monitoring and improving the Licensure Examination performance particularly in Teacher Education Institution (TEI). The study intends to offer a possible solution to most TEIs apprehensions regarding LET performance by providing the students of Teacher Education a student support service in the form of a personalized Learning Management System with performance prediction and recommendation capability. This can be developed through drawing data model using several data mining techniques and tools. Previous literature suggested using data mining to classify students, predict student performance, improve student retention, enhanced student achievement and assess complex students? behavior to name a few. This research project will provide the groundwork for th...","downloadable_attachments":[{"id":73257497,"asset_id":59225077,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":40135201,"first_name":"Mia","last_name":"Villarica","domain_name":"lspu","page_name":"MVillarica","display_name":"Mia Villarica","profile_url":"https://lspu.academia.edu/MVillarica?f_ri=23995","photo":"https://0.academia-photos.com/40135201/12148822/54104924/s65_mia.villarica.jpg"}],"research_interests":[{"id":19870,"name":"Research","url":"https://www.academia.edu/Documents/in/Research?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":555965,"name":"Advanced","url":"https://www.academia.edu/Documents/in/Advanced?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_56405948" data-work_id="56405948" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/56405948/The_Use_of_Data_Mining_to_Model_Personalized_Learning_Management_System">The Use of Data Mining to Model Personalized Learning Management System</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Licensure Examination performance is a growing concern of most of the educational institution because it is one of the determinants of quality education and validates high quality instruction. Educational institution is focused on... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_56405948" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Licensure Examination performance is a growing concern of most of the educational institution because it is one of the determinants of quality education and validates high quality instruction. Educational institution is focused on monitoring and improving the Licensure Examination performance particularly in Teacher Education Institution (TEI). The study intends to offer a possible solution to most TEIs apprehensions regarding LET performance by providing the students of Teacher Education a student support service in the form of a personalized Learning Management System with performance prediction and recommendation capability. This can be developed through drawing data model using several data mining techniques and tools. Previous literature suggested using data mining to classify students, predict student performance, improve student retention, enhanced student achievement and assess complex students? behavior to name a few. This research project will provide the groundwork for th...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/56405948" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="508be3012604fe19bddbe68f44cb9a2e" rel="nofollow" data-download="{"attachment_id":71808707,"asset_id":56405948,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/71808707/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="171427082" href="https://independent.academia.edu/MiaVillarVillarica">Mia Villar Villarica</a><script data-card-contents-for-user="171427082" type="text/json">{"id":171427082,"first_name":"Mia","last_name":"Villar Villarica","domain_name":"independent","page_name":"MiaVillarVillarica","display_name":"Mia Villar Villarica","profile_url":"https://independent.academia.edu/MiaVillarVillarica?f_ri=23995","photo":"https://0.academia-photos.com/171427082/65382602/53717990/s65_mia.villar_villarica.jpg"}</script></span></span></li><li class="js-paper-rank-work_56405948 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="56405948"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 56405948, container: ".js-paper-rank-work_56405948", }); });</script></li><li class="js-percentile-work_56405948 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 56405948; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_56405948"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_56405948 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="56405948"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56405948; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=56405948]").text(description); $(".js-view-count-work_56405948").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_56405948").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="56405948"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="19870" href="https://www.academia.edu/Documents/in/Research">Research</a>, <script data-card-contents-for-ri="19870" type="text/json">{"id":19870,"name":"Research","url":"https://www.academia.edu/Documents/in/Research?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="555965" href="https://www.academia.edu/Documents/in/Advanced">Advanced</a><script data-card-contents-for-ri="555965" type="text/json">{"id":555965,"name":"Advanced","url":"https://www.academia.edu/Documents/in/Advanced?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=56405948]'), work: {"id":56405948,"title":"The Use of Data Mining to Model Personalized Learning Management System","created_at":"2021-10-07T17:22:31.567-07:00","url":"https://www.academia.edu/56405948/The_Use_of_Data_Mining_to_Model_Personalized_Learning_Management_System?f_ri=23995","dom_id":"work_56405948","summary":"Licensure Examination performance is a growing concern of most of the educational institution because it is one of the determinants of quality education and validates high quality instruction. Educational institution is focused on monitoring and improving the Licensure Examination performance particularly in Teacher Education Institution (TEI). The study intends to offer a possible solution to most TEIs apprehensions regarding LET performance by providing the students of Teacher Education a student support service in the form of a personalized Learning Management System with performance prediction and recommendation capability. This can be developed through drawing data model using several data mining techniques and tools. Previous literature suggested using data mining to classify students, predict student performance, improve student retention, enhanced student achievement and assess complex students? behavior to name a few. This research project will provide the groundwork for th...","downloadable_attachments":[{"id":71808707,"asset_id":56405948,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":171427082,"first_name":"Mia","last_name":"Villar Villarica","domain_name":"independent","page_name":"MiaVillarVillarica","display_name":"Mia Villar Villarica","profile_url":"https://independent.academia.edu/MiaVillarVillarica?f_ri=23995","photo":"https://0.academia-photos.com/171427082/65382602/53717990/s65_mia.villar_villarica.jpg"}],"research_interests":[{"id":19870,"name":"Research","url":"https://www.academia.edu/Documents/in/Research?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":555965,"name":"Advanced","url":"https://www.academia.edu/Documents/in/Advanced?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_73899670" data-work_id="73899670" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/73899670/An_EDM_based_Multimodal_Method_for_Assessing_Learners_Affective_States_in_Collaborative_Crisis_Management_Serious_Games">An EDM-based Multimodal Method for Assessing Learners' Affective States in Collaborative Crisis Management Serious Games</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Recently, Crisis Management Serious Games (CMSG) have proved their potential for teaching both technical and soft skills related to managing crisis in a safe environment while reducing training costs. In order to improve learning outcomes... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_73899670" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Recently, Crisis Management Serious Games (CMSG) have proved their potential for teaching both technical and soft skills related to managing crisis in a safe environment while reducing training costs. In order to improve learning outcomes insured by CMSGs, many works focus on their evaluation. Despite its great interest, the learner emotional state is often neglected in the evaluation process. Indeed, negative emotions such as boredom or frustration degrade the learning quality since they frequently conduct to giving up the game. This research addresses this gap by combining gaming and affect aspects under an Educational Data Mining (EDM) approach to improve learning outcomes. Therefore, we propose an EDM-based multimodal method for assessing learners&#39; affective states by classifying data communicated in text messaging and facial expressions. This method is applied to assess learners&#39; engagement during a game-based collaborative evacuation scenario. The obtained assessment r...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/73899670" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="16ed704371d02364402b31c32659977c" rel="nofollow" data-download="{"attachment_id":82247146,"asset_id":73899670,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/82247146/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="41786878" href="https://univ-amu.academia.edu/BEspinasse">Bernard Espinasse</a><script data-card-contents-for-user="41786878" type="text/json">{"id":41786878,"first_name":"Bernard","last_name":"Espinasse","domain_name":"univ-amu","page_name":"BEspinasse","display_name":"Bernard Espinasse","profile_url":"https://univ-amu.academia.edu/BEspinasse?f_ri=23995","photo":"https://0.academia-photos.com/41786878/27727858/26026983/s65_bernard.espinasse.jpg"}</script></span></span></li><li class="js-paper-rank-work_73899670 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="73899670"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 73899670, container: ".js-paper-rank-work_73899670", }); });</script></li><li class="js-percentile-work_73899670 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 73899670; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_73899670"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_73899670 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="73899670"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 73899670; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=73899670]").text(description); $(".js-view-count-work_73899670").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_73899670").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="73899670"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=73899670]'), work: {"id":73899670,"title":"An EDM-based Multimodal Method for Assessing Learners' Affective States in Collaborative Crisis Management Serious Games","created_at":"2022-03-16T10:45:03.368-07:00","url":"https://www.academia.edu/73899670/An_EDM_based_Multimodal_Method_for_Assessing_Learners_Affective_States_in_Collaborative_Crisis_Management_Serious_Games?f_ri=23995","dom_id":"work_73899670","summary":"Recently, Crisis Management Serious Games (CMSG) have proved their potential for teaching both technical and soft skills related to managing crisis in a safe environment while reducing training costs. In order to improve learning outcomes insured by CMSGs, many works focus on their evaluation. Despite its great interest, the learner emotional state is often neglected in the evaluation process. Indeed, negative emotions such as boredom or frustration degrade the learning quality since they frequently conduct to giving up the game. This research addresses this gap by combining gaming and affect aspects under an Educational Data Mining (EDM) approach to improve learning outcomes. Therefore, we propose an EDM-based multimodal method for assessing learners\u0026#39; affective states by classifying data communicated in text messaging and facial expressions. This method is applied to assess learners\u0026#39; engagement during a game-based collaborative evacuation scenario. The obtained assessment r...","downloadable_attachments":[{"id":82247146,"asset_id":73899670,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":41786878,"first_name":"Bernard","last_name":"Espinasse","domain_name":"univ-amu","page_name":"BEspinasse","display_name":"Bernard Espinasse","profile_url":"https://univ-amu.academia.edu/BEspinasse?f_ri=23995","photo":"https://0.academia-photos.com/41786878/27727858/26026983/s65_bernard.espinasse.jpg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_8331662" data-work_id="8331662" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/8331662/SESSION_TIMEOUT_THRESHOLDS_IMPACT_ON_QUALITY_AND_QUANTITY_OF_EXTRACTED_SEQUENCE_RULES">SESSION TIMEOUT THRESHOLDS IMPACT ON QUALITY AND QUANTITY OF EXTRACTED SEQUENCE RULES</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The effort of using web usage mining methods in the area of educational data mining is to reveal the knowledge hidden in the log files of the web and database servers of contemporary virtual learning environments. By applying data mining... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_8331662" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The effort of using web usage mining methods in the area of educational data mining is to reveal the knowledge hidden in<br />the log files of the web and database servers of contemporary virtual learning environments. By applying data mining methods to these data, interesting patterns concerning the students’ behavior can be<br />identified. These methods help us to find the most effective structure of the e-learning courses, optimize the learning content,<br />recommend the most suitable learning path based on student’s behavior or provide more personalized learning environment. We<br />prepared six datasets of different quality obtained from logs of the virtual learning environment Moodle and pre-processed in<br />different ways. We used three datasets with identified users’ sessions based on 15, 30 and 60 minute session timeout threshold and<br />three another datasets with the same thresholds including reconstructed paths among course activities. We tried to assess<br />the impact of different session timeout thresholds with or without paths completion on the quantity and quality of the sequence<br />rules that contribute to the representation of the students’ behavioral patterns in virtual learning environment. The results show that<br />the session timeout threshold has significant impact on quality and quantity of extracted sequence rules. On the contrary, it is shown<br />that the completion of paths has neither significant impact on quantity nor quality of extracted rules.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/8331662" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="95b3c10d7be300d0eac5f4d39ba9e7a0" rel="nofollow" data-download="{"attachment_id":34736293,"asset_id":8331662,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/34736293/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2657630" href="https://sdiwc.academia.edu/TheSocietyofDigitalInformationandWirelessCommunications">SDIWC Organization</a><script data-card-contents-for-user="2657630" type="text/json">{"id":2657630,"first_name":"SDIWC","last_name":"Organization","domain_name":"sdiwc","page_name":"TheSocietyofDigitalInformationandWirelessCommunications","display_name":"SDIWC Organization","profile_url":"https://sdiwc.academia.edu/TheSocietyofDigitalInformationandWirelessCommunications?f_ri=23995","photo":"https://0.academia-photos.com/2657630/849179/1055710/s65_natalie.walker.jpg"}</script></span></span></li><li class="js-paper-rank-work_8331662 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="8331662"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 8331662, container: ".js-paper-rank-work_8331662", }); });</script></li><li class="js-percentile-work_8331662 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 8331662; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_8331662"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_8331662 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="8331662"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 8331662; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=8331662]").text(description); $(".js-view-count-work_8331662").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_8331662").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="8331662"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="218582" href="https://www.academia.edu/Documents/in/Time_Windows">Time Windows</a>, <script data-card-contents-for-ri="218582" type="text/json">{"id":218582,"name":"Time Windows","url":"https://www.academia.edu/Documents/in/Time_Windows?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1554020" href="https://www.academia.edu/Documents/in/Session_Timeout_Threshold">Session Timeout Threshold</a>, <script data-card-contents-for-ri="1554020" type="text/json">{"id":1554020,"name":"Session Timeout Threshold","url":"https://www.academia.edu/Documents/in/Session_Timeout_Threshold?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1554021" href="https://www.academia.edu/Documents/in/Path_Completion">Path Completion</a><script data-card-contents-for-ri="1554021" type="text/json">{"id":1554021,"name":"Path Completion","url":"https://www.academia.edu/Documents/in/Path_Completion?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=8331662]'), work: {"id":8331662,"title":"SESSION TIMEOUT THRESHOLDS IMPACT ON QUALITY AND QUANTITY OF EXTRACTED SEQUENCE RULES","created_at":"2014-09-15T00:58:05.192-07:00","url":"https://www.academia.edu/8331662/SESSION_TIMEOUT_THRESHOLDS_IMPACT_ON_QUALITY_AND_QUANTITY_OF_EXTRACTED_SEQUENCE_RULES?f_ri=23995","dom_id":"work_8331662","summary":"The effort of using web usage mining methods in the area of educational data mining is to reveal the knowledge hidden in\nthe log files of the web and database servers of contemporary virtual learning environments. By applying data mining methods to these data, interesting patterns concerning the students’ behavior can be\nidentified. These methods help us to find the most effective structure of the e-learning courses, optimize the learning content,\nrecommend the most suitable learning path based on student’s behavior or provide more personalized learning environment. We\nprepared six datasets of different quality obtained from logs of the virtual learning environment Moodle and pre-processed in\ndifferent ways. We used three datasets with identified users’ sessions based on 15, 30 and 60 minute session timeout threshold and\nthree another datasets with the same thresholds including reconstructed paths among course activities. We tried to assess\nthe impact of different session timeout thresholds with or without paths completion on the quantity and quality of the sequence\nrules that contribute to the representation of the students’ behavioral patterns in virtual learning environment. The results show that\nthe session timeout threshold has significant impact on quality and quantity of extracted sequence rules. On the contrary, it is shown\nthat the completion of paths has neither significant impact on quantity nor quality of extracted rules.","downloadable_attachments":[{"id":34736293,"asset_id":8331662,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":2657630,"first_name":"SDIWC","last_name":"Organization","domain_name":"sdiwc","page_name":"TheSocietyofDigitalInformationandWirelessCommunications","display_name":"SDIWC Organization","profile_url":"https://sdiwc.academia.edu/TheSocietyofDigitalInformationandWirelessCommunications?f_ri=23995","photo":"https://0.academia-photos.com/2657630/849179/1055710/s65_natalie.walker.jpg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":218582,"name":"Time Windows","url":"https://www.academia.edu/Documents/in/Time_Windows?f_ri=23995","nofollow":false},{"id":1554020,"name":"Session Timeout Threshold","url":"https://www.academia.edu/Documents/in/Session_Timeout_Threshold?f_ri=23995","nofollow":false},{"id":1554021,"name":"Path Completion","url":"https://www.academia.edu/Documents/in/Path_Completion?f_ri=23995","nofollow":false},{"id":1554022,"name":"Sequence Rules Analysis","url":"https://www.academia.edu/Documents/in/Sequence_Rules_Analysis?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_75316955" data-work_id="75316955" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/75316955/Multiple_instance_learning_for_classifying_students_in_learning_management_systems">Multiple instance learning for classifying students in learning management systems</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/75316955" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c949af14fa08173c4bbfdc29ea26d60c" rel="nofollow" data-download="{"attachment_id":83133752,"asset_id":75316955,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/83133752/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="22425" href="https://uco-es.academia.edu/Crist%C3%B3balRomero">Cristóbal Romero</a><script data-card-contents-for-user="22425" type="text/json">{"id":22425,"first_name":"Cristóbal","last_name":"Romero","domain_name":"uco-es","page_name":"CristóbalRomero","display_name":"Cristóbal Romero","profile_url":"https://uco-es.academia.edu/Crist%C3%B3balRomero?f_ri=23995","photo":"https://0.academia-photos.com/22425/7510/7171/s65_crist_bal.romero.gif"}</script></span></span></li><li class="js-paper-rank-work_75316955 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="75316955"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 75316955, container: ".js-paper-rank-work_75316955", }); });</script></li><li class="js-percentile-work_75316955 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75316955; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_75316955"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_75316955 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="75316955"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75316955; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75316955]").text(description); $(".js-view-count-work_75316955").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_75316955").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="75316955"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">9</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="465" href="https://www.academia.edu/Documents/in/Artificial_Intelligence">Artificial Intelligence</a>, <script data-card-contents-for-ri="465" type="text/json">{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="20952" href="https://www.academia.edu/Documents/in/Multiple_Instance_Learning">Multiple Instance Learning</a><script data-card-contents-for-ri="20952" type="text/json">{"id":20952,"name":"Multiple Instance Learning","url":"https://www.academia.edu/Documents/in/Multiple_Instance_Learning?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=75316955]'), work: {"id":75316955,"title":"Multiple instance learning for classifying students in learning management systems","created_at":"2022-04-03T07:06:05.079-07:00","url":"https://www.academia.edu/75316955/Multiple_instance_learning_for_classifying_students_in_learning_management_systems?f_ri=23995","dom_id":"work_75316955","summary":null,"downloadable_attachments":[{"id":83133752,"asset_id":75316955,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":22425,"first_name":"Cristóbal","last_name":"Romero","domain_name":"uco-es","page_name":"CristóbalRomero","display_name":"Cristóbal Romero","profile_url":"https://uco-es.academia.edu/Crist%C3%B3balRomero?f_ri=23995","photo":"https://0.academia-photos.com/22425/7510/7171/s65_crist_bal.romero.gif"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=23995","nofollow":false},{"id":2008,"name":"Machine 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students</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/77245062" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="77e9ec4ba8dc25a7e2e91c37805d696e" rel="nofollow" data-download="{"attachment_id":84679177,"asset_id":77245062,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" 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data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=77245062]'), work: {"id":77245062,"title":"Data mining algorithms to classify 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Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":713079,"name":"University Student","url":"https://www.academia.edu/Documents/in/University_Student?f_ri=23995"},{"id":3808434,"name":"Data mining Algorithm","url":"https://www.academia.edu/Documents/in/Data_mining_Algorithm?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_44660148 coauthored" data-work_id="44660148" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/44660148/Analysis_of_Popular_Techniques_Used_in_Educational_Data_Mining">Analysis of Popular Techniques Used in Educational Data Mining</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The importance of data mining is increasing in education field as it can help both in the improvement of education system and in the growth of students by making predictions. Educational Data Mining (EDM) is a young interdisciplinary... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_44660148" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The importance of data mining is increasing in education field as it can help both in the improvement of education<br />system and in the growth of students by making predictions. Educational Data Mining (EDM) is a young<br />interdisciplinary work field that helps to deal with the data related to educational perspective. Today, educational<br />institutions collect and archive massive quantities of data, such as students registration, attendance as well as<br />the exam results. Mining of this data helps the institutions to understand students behaviour and interests by<br />extracting all the useful information from the huge data available. Dierent data mining techniques are being used<br />for mining the data in educational eld. Now days, the Articial Intelligence and Machine Learning techniques are<br />more popular among the researchers to extract the information from the educational databases, as these provide<br />more reliable results as compared to other techniques. In this paper, many popular data mining techniques have<br />been reviewed that are being applied on the educational data to solve the different problems faced by the students<br />so as to improve the learning outcomes of the students</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/44660148" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="cae8385086c81c22ffafbb2ea1bf87f8" rel="nofollow" data-download="{"attachment_id":65132273,"asset_id":44660148,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/65132273/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33023523" href="https://igu.academia.edu/SatinderBalGupta">Satinder Bal Gupta</a><script data-card-contents-for-user="33023523" type="text/json">{"id":33023523,"first_name":"Satinder Bal","last_name":"Gupta","domain_name":"igu","page_name":"SatinderBalGupta","display_name":"Satinder Bal Gupta","profile_url":"https://igu.academia.edu/SatinderBalGupta?f_ri=23995","photo":"https://0.academia-photos.com/33023523/9810896/10955764/s65_satinder_bal.gupta.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-44660148">+1</span><div class="hidden js-additional-users-44660148"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/shivanigupta325">shivani gupta</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-44660148'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-44660148').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_44660148 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="44660148"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 44660148; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=44660148]").text(description); $(".js-view-count-work_44660148").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_44660148").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="44660148"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="60650" href="https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining">Data Warehousing and Data Mining</a>, <script data-card-contents-for-ri="60650" type="text/json">{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="413148" href="https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining">Big Data / Analytics / Data Mining</a><script data-card-contents-for-ri="413148" type="text/json">{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=44660148]'), work: {"id":44660148,"title":"Analysis of Popular Techniques Used in Educational Data Mining","created_at":"2020-12-08T04:09:22.693-08:00","url":"https://www.academia.edu/44660148/Analysis_of_Popular_Techniques_Used_in_Educational_Data_Mining?f_ri=23995","dom_id":"work_44660148","summary":"The importance of data mining is increasing in education \ffield as it can help both in the improvement of education\nsystem and in the growth of students by making predictions. Educational Data Mining (EDM) is a young\ninterdisciplinary work fi\feld that helps to deal with the data related to educational perspective. Today, educational\ninstitutions collect and archive massive quantities of data, such as students registration, attendance as well as\nthe exam results. Mining of this data helps the institutions to understand students behaviour and interests by\nextracting all the useful information from the huge data available. Di\u000berent data mining techniques are being used\nfor mining the data in educational \feld. Now days, the Arti\fcial Intelligence and Machine Learning techniques are\nmore popular among the researchers to extract the information from the educational databases, as these provide\nmore reliable results as compared to other techniques. In this paper, many popular data mining techniques have\nbeen reviewed that are being applied on the educational data to solve the different problems faced by the students\nso as to improve the learning outcomes of the students","downloadable_attachments":[{"id":65132273,"asset_id":44660148,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33023523,"first_name":"Satinder Bal","last_name":"Gupta","domain_name":"igu","page_name":"SatinderBalGupta","display_name":"Satinder Bal Gupta","profile_url":"https://igu.academia.edu/SatinderBalGupta?f_ri=23995","photo":"https://0.academia-photos.com/33023523/9810896/10955764/s65_satinder_bal.gupta.jpg"},{"id":160364792,"first_name":"shivani","last_name":"gupta","domain_name":"independent","page_name":"shivanigupta325","display_name":"shivani gupta","profile_url":"https://independent.academia.edu/shivanigupta325?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995","nofollow":false},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_77434715" data-work_id="77434715" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/77434715/Educational_data_sciences">Educational data sciences</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/77434715" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="2cad84f2b82f9eb601c83cf17434f8c4" rel="nofollow" data-download="{"attachment_id":84801912,"asset_id":77434715,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/84801912/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="14205815" href="https://independent.academia.edu/PPiety">Philip Piety</a><script data-card-contents-for-user="14205815" type="text/json">{"id":14205815,"first_name":"Philip","last_name":"Piety","domain_name":"independent","page_name":"PPiety","display_name":"Philip Piety","profile_url":"https://independent.academia.edu/PPiety?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_77434715 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="77434715"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 77434715, container: ".js-paper-rank-work_77434715", }); 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$(".js-view-count[data-work-id=77434715]").text(description); $(".js-view-count-work_77434715").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_77434715").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="77434715"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">13</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="922" href="https://www.academia.edu/Documents/in/Education">Education</a>, <script data-card-contents-for-ri="922" type="text/json">{"id":922,"name":"Education","url":"https://www.academia.edu/Documents/in/Education?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1000" href="https://www.academia.edu/Documents/in/Instructional_Design">Instructional Design</a>, <script data-card-contents-for-ri="1000" type="text/json">{"id":1000,"name":"Instructional Design","url":"https://www.academia.edu/Documents/in/Instructional_Design?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1003" href="https://www.academia.edu/Documents/in/Educational_Technology">Educational Technology</a><script data-card-contents-for-ri="1003" type="text/json">{"id":1003,"name":"Educational Technology","url":"https://www.academia.edu/Documents/in/Educational_Technology?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=77434715]'), work: {"id":77434715,"title":"Educational data sciences","created_at":"2022-04-24T02:59:18.447-07:00","url":"https://www.academia.edu/77434715/Educational_data_sciences?f_ri=23995","dom_id":"work_77434715","summary":null,"downloadable_attachments":[{"id":84801912,"asset_id":77434715,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":14205815,"first_name":"Philip","last_name":"Piety","domain_name":"independent","page_name":"PPiety","display_name":"Philip Piety","profile_url":"https://independent.academia.edu/PPiety?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false},{"id":922,"name":"Education","url":"https://www.academia.edu/Documents/in/Education?f_ri=23995","nofollow":false},{"id":1000,"name":"Instructional Design","url":"https://www.academia.edu/Documents/in/Instructional_Design?f_ri=23995","nofollow":false},{"id":1003,"name":"Educational Technology","url":"https://www.academia.edu/Documents/in/Educational_Technology?f_ri=23995","nofollow":false},{"id":1601,"name":"Teacher Education","url":"https://www.academia.edu/Documents/in/Teacher_Education?f_ri=23995"},{"id":1654,"name":"Sociotechnical Systems","url":"https://www.academia.edu/Documents/in/Sociotechnical_Systems?f_ri=23995"},{"id":2621,"name":"Higher Education","url":"https://www.academia.edu/Documents/in/Higher_Education?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":54344,"name":"Methods","url":"https://www.academia.edu/Documents/in/Methods?f_ri=23995"},{"id":126300,"name":"Big Data","url":"https://www.academia.edu/Documents/in/Big_Data?f_ri=23995"},{"id":439576,"name":"Acm","url":"https://www.academia.edu/Documents/in/Acm?f_ri=23995"},{"id":580597,"name":"Data driven decisions","url":"https://www.academia.edu/Documents/in/Data_driven_decisions?f_ri=23995"},{"id":1198660,"name":"E Learning","url":"https://www.academia.edu/Documents/in/E_Learning-14?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_49450444" data-work_id="49450444" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/49450444/Cryptosystem_for_Secured_E_Learning_and_Educational_Data_Mining_in_Higher_Education">Cryptosystem for Secured E-Learning and Educational Data Mining in Higher Education</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In the 21st century, we have plenty of data available in the society of education. Importantly, today's education system has changed, it takes place through all the available channels and one of the significant means is the digital... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_49450444" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In the 21st century, we have plenty of data available in the society of education. Importantly, today's education system has changed, it takes place through all the available channels and one of the significant means is the digital learning e-learning. Large amounts of data are available for the students as well as teachers to access the digital data online. Today security of the data became an important concern in the society and at the education sector level. Further, we need to extract the precise data and improve the existing education system through e-learning by using Educational Data Mining. In this paper, we will focus on the security of the online education resources and the extraction of the data based on the student's level by using the mining techniques that will be helpful for the students.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/49450444" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="eb54c3c1dac8ba8f9be40f005d6bd306" rel="nofollow" data-download="{"attachment_id":67799227,"asset_id":49450444,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/67799227/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="62901029" href="https://independent.academia.edu/PublishingIndiaGroup">Publishing India Group</a><script data-card-contents-for-user="62901029" type="text/json">{"id":62901029,"first_name":"Publishing India","last_name":"Group","domain_name":"independent","page_name":"PublishingIndiaGroup","display_name":"Publishing India Group","profile_url":"https://independent.academia.edu/PublishingIndiaGroup?f_ri=23995","photo":"https://0.academia-photos.com/62901029/42365669/34018621/s65_publishing_india.group.jpg"}</script></span></span></li><li class="js-paper-rank-work_49450444 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="49450444"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 49450444, container: ".js-paper-rank-work_49450444", }); 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$(".js-view-count[data-work-id=49450444]").text(description); $(".js-view-count-work_49450444").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_49450444").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="49450444"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="1283" href="https://www.academia.edu/Documents/in/Information_Security">Information Security</a>, <script data-card-contents-for-ri="1283" type="text/json">{"id":1283,"name":"Information Security","url":"https://www.academia.edu/Documents/in/Information_Security?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1609" href="https://www.academia.edu/Documents/in/E-learning">E-learning</a>, <script data-card-contents-for-ri="1609" type="text/json">{"id":1609,"name":"E-learning","url":"https://www.academia.edu/Documents/in/E-learning?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="13923" href="https://www.academia.edu/Documents/in/Computer_Security">Computer Security</a>, <script data-card-contents-for-ri="13923" type="text/json">{"id":13923,"name":"Computer Security","url":"https://www.academia.edu/Documents/in/Computer_Security?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="16542" href="https://www.academia.edu/Documents/in/Cryptography">Cryptography</a><script data-card-contents-for-ri="16542" type="text/json">{"id":16542,"name":"Cryptography","url":"https://www.academia.edu/Documents/in/Cryptography?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=49450444]'), work: {"id":49450444,"title":"Cryptosystem for Secured E-Learning and Educational Data Mining in Higher Education","created_at":"2021-06-29T02:05:22.698-07:00","url":"https://www.academia.edu/49450444/Cryptosystem_for_Secured_E_Learning_and_Educational_Data_Mining_in_Higher_Education?f_ri=23995","dom_id":"work_49450444","summary":"In the 21st century, we have plenty of data available in the society of education. Importantly, today's education system has changed, it takes place through all the available channels and one of the significant means is the digital learning e-learning. Large amounts of data are available for the students as well as teachers to access the digital data online. Today security of the data became an important concern in the society and at the education sector level. Further, we need to extract the precise data and improve the existing education system through e-learning by using Educational Data Mining. In this paper, we will focus on the security of the online education resources and the extraction of the data based on the student's level by using the mining techniques that will be helpful for the students.","downloadable_attachments":[{"id":67799227,"asset_id":49450444,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":62901029,"first_name":"Publishing India","last_name":"Group","domain_name":"independent","page_name":"PublishingIndiaGroup","display_name":"Publishing India Group","profile_url":"https://independent.academia.edu/PublishingIndiaGroup?f_ri=23995","photo":"https://0.academia-photos.com/62901029/42365669/34018621/s65_publishing_india.group.jpg"}],"research_interests":[{"id":1283,"name":"Information Security","url":"https://www.academia.edu/Documents/in/Information_Security?f_ri=23995","nofollow":false},{"id":1609,"name":"E-learning","url":"https://www.academia.edu/Documents/in/E-learning?f_ri=23995","nofollow":false},{"id":13923,"name":"Computer Security","url":"https://www.academia.edu/Documents/in/Computer_Security?f_ri=23995","nofollow":false},{"id":16542,"name":"Cryptography","url":"https://www.academia.edu/Documents/in/Cryptography?f_ri=23995","nofollow":false},{"id":21903,"name":"Encryption","url":"https://www.academia.edu/Documents/in/Encryption?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":4010968,"name":"KDED (Knowledge Discovery in Educational Databases)","url":"https://www.academia.edu/Documents/in/KDED_Knowledge_Discovery_in_Educational_Databases_?f_ri=23995"},{"id":4010969,"name":"Threats and Risks","url":"https://www.academia.edu/Documents/in/Threats_and_Risks?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_31006269" data-work_id="31006269" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/31006269/A_BINARY_BAT_INSPIRED_ALGORITHM_FOR_THE_CLASSIFICATION_OF_BREAST_CANCER_DATA">A BINARY BAT INSPIRED ALGORITHM FOR THE CLASSIFICATION OF BREAST CANCER DATA</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Advancement in information and technology has made a major impact on medical science where the researchers come up with new ideas for improving the classification rate of various diseases. Breast cancer is one such disease killing large... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_31006269" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Advancement in information and technology has made a major impact on medical science where the researchers come up with new ideas for improving the classification rate of various diseases. Breast cancer is one such disease killing large number of people around the world. Diagnosing the disease at its earliest instance makes a huge impact on its treatment. The authors propose a Binary Bat Algorithm (BBA) based Feedforward Neural Network (FNN) hybrid model, where the advantages of BBA and efficiency of FNN is exploited for the classification of three benchmark breast cancer datasets into malignant and benign cases. Here BBA is used to generate a V-shaped hyperbolic tangent function for training the network and a fitness function is used for error minimization. FNNBBA based classification produces 92.61% accuracy for training data and 89.95% for testing data.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/31006269" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d17f365f56decddfa9b0775b18bff906" rel="nofollow" data-download="{"attachment_id":59097855,"asset_id":31006269,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/59097855/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="21109123" href="https://independent.academia.edu/ijscaijournal">International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)</a><script data-card-contents-for-user="21109123" type="text/json">{"id":21109123,"first_name":"International Journal on Soft Computing, Artificial Intelligence and Applications","last_name":"(IJSCAI)","domain_name":"independent","page_name":"ijscaijournal","display_name":"International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)","profile_url":"https://independent.academia.edu/ijscaijournal?f_ri=23995","photo":"https://0.academia-photos.com/21109123/9710763/110171411/s65_international_journal_on_soft_computing_artificial_intelligence_and_applications._ijscai_.jpg"}</script></span></span></li><li class="js-paper-rank-work_31006269 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="31006269"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 31006269, container: ".js-paper-rank-work_31006269", }); });</script></li><li class="js-percentile-work_31006269 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 31006269; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_31006269"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_31006269 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="31006269"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 31006269; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=31006269]").text(description); $(".js-view-count-work_31006269").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_31006269").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="31006269"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">19</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="1440" href="https://www.academia.edu/Documents/in/Visualization">Visualization</a>, <script data-card-contents-for-ri="1440" type="text/json">{"id":1440,"name":"Visualization","url":"https://www.academia.edu/Documents/in/Visualization?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1681" href="https://www.academia.edu/Documents/in/Decision_Making">Decision Making</a>, <script data-card-contents-for-ri="1681" type="text/json">{"id":1681,"name":"Decision Making","url":"https://www.academia.edu/Documents/in/Decision_Making?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="3424" href="https://www.academia.edu/Documents/in/Information_Visualization">Information Visualization</a><script data-card-contents-for-ri="3424" type="text/json">{"id":3424,"name":"Information Visualization","url":"https://www.academia.edu/Documents/in/Information_Visualization?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=31006269]'), work: {"id":31006269,"title":"A BINARY BAT INSPIRED ALGORITHM FOR THE CLASSIFICATION OF BREAST CANCER DATA","created_at":"2017-01-20T02:01:59.329-08:00","url":"https://www.academia.edu/31006269/A_BINARY_BAT_INSPIRED_ALGORITHM_FOR_THE_CLASSIFICATION_OF_BREAST_CANCER_DATA?f_ri=23995","dom_id":"work_31006269","summary":"Advancement in information and technology has made a major impact on medical science where the researchers come up with new ideas for improving the classification rate of various diseases. Breast cancer is one such disease killing large number of people around the world. Diagnosing the disease at its earliest instance makes a huge impact on its treatment. The authors propose a Binary Bat Algorithm (BBA) based Feedforward Neural Network (FNN) hybrid model, where the advantages of BBA and efficiency of FNN is exploited for the classification of three benchmark breast cancer datasets into malignant and benign cases. Here BBA is used to generate a V-shaped hyperbolic tangent function for training the network and a fitness function is used for error minimization. FNNBBA based classification produces 92.61% accuracy for training data and 89.95% for testing data.","downloadable_attachments":[{"id":59097855,"asset_id":31006269,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":21109123,"first_name":"International Journal on Soft Computing, Artificial Intelligence and Applications","last_name":"(IJSCAI)","domain_name":"independent","page_name":"ijscaijournal","display_name":"International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)","profile_url":"https://independent.academia.edu/ijscaijournal?f_ri=23995","photo":"https://0.academia-photos.com/21109123/9710763/110171411/s65_international_journal_on_soft_computing_artificial_intelligence_and_applications._ijscai_.jpg"}],"research_interests":[{"id":1440,"name":"Visualization","url":"https://www.academia.edu/Documents/in/Visualization?f_ri=23995","nofollow":false},{"id":1681,"name":"Decision Making","url":"https://www.academia.edu/Documents/in/Decision_Making?f_ri=23995","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":3424,"name":"Information Visualization","url":"https://www.academia.edu/Documents/in/Information_Visualization?f_ri=23995","nofollow":false},{"id":5486,"name":"Clustering and Classification Methods","url":"https://www.academia.edu/Documents/in/Clustering_and_Classification_Methods?f_ri=23995"},{"id":8210,"name":"Behavioral Decision Making","url":"https://www.academia.edu/Documents/in/Behavioral_Decision_Making?f_ri=23995"},{"id":14494,"name":"Opinion Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Opinion_Mining_Data_Mining_?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":32701,"name":"Data Mining in Bioinformatics","url":"https://www.academia.edu/Documents/in/Data_Mining_in_Bioinformatics?f_ri=23995"},{"id":39693,"name":"Distributed Data Mining","url":"https://www.academia.edu/Documents/in/Distributed_Data_Mining?f_ri=23995"},{"id":47980,"name":"Data Visualization","url":"https://www.academia.edu/Documents/in/Data_Visualization?f_ri=23995"},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995"},{"id":93455,"name":"Infographics and data visualization","url":"https://www.academia.edu/Documents/in/Infographics_and_data_visualization?f_ri=23995"},{"id":99804,"name":"Privacy Preserving Data Mining","url":"https://www.academia.edu/Documents/in/Privacy_Preserving_Data_Mining?f_ri=23995"},{"id":106145,"name":"Classification","url":"https://www.academia.edu/Documents/in/Classification?f_ri=23995"},{"id":191248,"name":"Medical Data Mining using Soft Computing","url":"https://www.academia.edu/Documents/in/Medical_Data_Mining_using_Soft_Computing?f_ri=23995"},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995"},{"id":721504,"name":"Medical Data Mining","url":"https://www.academia.edu/Documents/in/Medical_Data_Mining?f_ri=23995"},{"id":2618118,"name":"Binary Bat","url":"https://www.academia.edu/Documents/in/Binary_Bat?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_49410658" data-work_id="49410658" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/49410658/Learning_Analytics_as_a_Tool_for_Visual_Analysis_in_an_Open_Data_Environment_A_Higher_Education_Case">Learning Analytics as a Tool for Visual Analysis in an Open Data Environment: A Higher Education Case</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In the past few years, the data analysis in the academic field has gained interest, because higher education institutions generate large volumes of information through historic data of students, information systems and the tools used by... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_49410658" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In the past few years, the data analysis in the academic field has gained interest, because higher education institutions generate large volumes of information through historic data of students, information systems and the tools used by the learning processes. The analysis of this information supports the decision making, which positively impacts the academic performance of students and teachers. In addition, if the results of the analysis are shared with the institution community, it is possible to individualize the needs of the students and professors. Thus, the professional improving process can be applied to each person. This analysis needs to be focused on an education context such as Learning Analytics (LA) and Education Data Mining (EDM), which address the Knowledge Discovery process (KDP). Because of this, we present in this paper the implementation of LA in an Open Data (OD) environment to analyze the information of a higher education institution. The analysis is focused on the academic performance of the students from different perspectives (social, economic, family, among others). In order to improve the results, the analysis process is done in real time through Web Analytics (WA) for each member of the institution according to its needs.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/49410658" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="488bf22b33812a5a9cbd18b05a8b7bfa" rel="nofollow" data-download="{"attachment_id":67769469,"asset_id":49410658,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/67769469/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="12649511" href="https://ugr.academia.edu/JohnnyAlexanderSalazarCardona">Johnny Alexander Salazar Cardona</a><script data-card-contents-for-user="12649511" type="text/json">{"id":12649511,"first_name":"Johnny Alexander","last_name":"Salazar Cardona","domain_name":"ugr","page_name":"JohnnyAlexanderSalazarCardona","display_name":"Johnny Alexander Salazar Cardona","profile_url":"https://ugr.academia.edu/JohnnyAlexanderSalazarCardona?f_ri=23995","photo":"https://0.academia-photos.com/12649511/7409678/149671072/s65_johnny_alexander.salazar_cardona.jpg"}</script></span></span></li><li class="js-paper-rank-work_49410658 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="49410658"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 49410658, container: ".js-paper-rank-work_49410658", }); });</script></li><li class="js-percentile-work_49410658 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 49410658; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_49410658"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_49410658 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="49410658"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 49410658; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=49410658]").text(description); $(".js-view-count-work_49410658").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_49410658").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="49410658"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="24212" href="https://www.academia.edu/Documents/in/Open_Data">Open Data</a>, <script data-card-contents-for-ri="24212" type="text/json">{"id":24212,"name":"Open Data","url":"https://www.academia.edu/Documents/in/Open_Data?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="46289" href="https://www.academia.edu/Documents/in/Web_analytics">Web analytics</a>, <script data-card-contents-for-ri="46289" type="text/json">{"id":46289,"name":"Web analytics","url":"https://www.academia.edu/Documents/in/Web_analytics?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="78457" href="https://www.academia.edu/Documents/in/Learning_Analytics">Learning Analytics</a><script data-card-contents-for-ri="78457" type="text/json">{"id":78457,"name":"Learning Analytics","url":"https://www.academia.edu/Documents/in/Learning_Analytics?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=49410658]'), work: {"id":49410658,"title":"Learning Analytics as a Tool for Visual Analysis in an Open Data Environment: A Higher Education Case","created_at":"2021-06-26T16:50:28.534-07:00","url":"https://www.academia.edu/49410658/Learning_Analytics_as_a_Tool_for_Visual_Analysis_in_an_Open_Data_Environment_A_Higher_Education_Case?f_ri=23995","dom_id":"work_49410658","summary":"In the past few years, the data analysis in the academic field has gained interest, because higher education institutions generate large volumes of information through historic data of students, information systems and the tools used by the learning processes. The analysis of this information supports the decision making, which positively impacts the academic performance of students and teachers. In addition, if the results of the analysis are shared with the institution community, it is possible to individualize the needs of the students and professors. Thus, the professional improving process can be applied to each person. This analysis needs to be focused on an education context such as Learning Analytics (LA) and Education Data Mining (EDM), which address the Knowledge Discovery process (KDP). Because of this, we present in this paper the implementation of LA in an Open Data (OD) environment to analyze the information of a higher education institution. The analysis is focused on the academic performance of the students from different perspectives (social, economic, family, among others). In order to improve the results, the analysis process is done in real time through Web Analytics (WA) for each member of the institution according to its needs.","downloadable_attachments":[{"id":67769469,"asset_id":49410658,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":12649511,"first_name":"Johnny Alexander","last_name":"Salazar Cardona","domain_name":"ugr","page_name":"JohnnyAlexanderSalazarCardona","display_name":"Johnny Alexander Salazar Cardona","profile_url":"https://ugr.academia.edu/JohnnyAlexanderSalazarCardona?f_ri=23995","photo":"https://0.academia-photos.com/12649511/7409678/149671072/s65_johnny_alexander.salazar_cardona.jpg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":24212,"name":"Open Data","url":"https://www.academia.edu/Documents/in/Open_Data?f_ri=23995","nofollow":false},{"id":46289,"name":"Web analytics","url":"https://www.academia.edu/Documents/in/Web_analytics?f_ri=23995","nofollow":false},{"id":78457,"name":"Learning Analytics","url":"https://www.academia.edu/Documents/in/Learning_Analytics?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_44722097" data-work_id="44722097" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/44722097/Prediction_Students_Performance_in_Elective_Subject_Using_Decision_Tree_Method">Prediction Students' Performance in Elective Subject Using Decision Tree Method</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In polytechnic system, a student must take the elective subjects at least 3 subjects to complete their study. The elective subjects were chosen based on their interest and first come first serve. The result obtained for elective subjects... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_44722097" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In polytechnic system, a student must take the elective subjects at least 3 subjects to complete their study. The elective subjects were chosen based on their interest and first come first serve. The result obtained for elective subjects in final examination will affect their future. It is important to predict whether they pass or fail in final examination. Literature survey (LS) was used to obtain the information about students' profile and current approaches in predicting the students' performance using data mining. In this paper, the researcher uses data mining which is decision tree method to predict the students' performance in elective subject. The aim of this research is to evaluate the students result in choosing the correct elective subjects. This research is focused on the ICT students who select DBM3033 as an elective subject. Two phases involved which are prepossessing data and mining data. RapidMiner software is used in mining data process. Classification technique is applied for decision tree method. The research findings showed that students whose result weak in both SPM Mathematics and DBM1033 are predicted as fail in final examination for DBM3033.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/44722097" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="da3d1b88eb5a19943fda7dd563f57811" rel="nofollow" data-download="{"attachment_id":65204146,"asset_id":44722097,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/65204146/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="181511182" href="https://puo.academia.edu/suhainybintisulaiman">suhainy binti sulaiman</a><script data-card-contents-for-user="181511182" type="text/json">{"id":181511182,"first_name":"suhainy","last_name":"binti sulaiman","domain_name":"puo","page_name":"suhainybintisulaiman","display_name":"suhainy binti sulaiman","profile_url":"https://puo.academia.edu/suhainybintisulaiman?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_44722097 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="44722097"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 44722097, container: ".js-paper-rank-work_44722097", }); });</script></li><li class="js-percentile-work_44722097 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 44722097; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_44722097"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_44722097 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="44722097"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 44722097; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=44722097]").text(description); $(".js-view-count-work_44722097").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_44722097").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="44722097"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4095" href="https://www.academia.edu/Documents/in/Classification_Machine_Learning_">Classification (Machine Learning)</a>, <script data-card-contents-for-ri="4095" type="text/json">{"id":4095,"name":"Classification (Machine Learning)","url":"https://www.academia.edu/Documents/in/Classification_Machine_Learning_?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="162271" href="https://www.academia.edu/Documents/in/Decision_Tree">Decision Tree</a><script data-card-contents-for-ri="162271" type="text/json">{"id":162271,"name":"Decision Tree","url":"https://www.academia.edu/Documents/in/Decision_Tree?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=44722097]'), work: {"id":44722097,"title":"Prediction Students' Performance in Elective Subject Using Decision Tree Method","created_at":"2020-12-17T00:19:02.740-08:00","url":"https://www.academia.edu/44722097/Prediction_Students_Performance_in_Elective_Subject_Using_Decision_Tree_Method?f_ri=23995","dom_id":"work_44722097","summary":"In polytechnic system, a student must take the elective subjects at least 3 subjects to complete their study. The elective subjects were chosen based on their interest and first come first serve. The result obtained for elective subjects in final examination will affect their future. It is important to predict whether they pass or fail in final examination. Literature survey (LS) was used to obtain the information about students' profile and current approaches in predicting the students' performance using data mining. In this paper, the researcher uses data mining which is decision tree method to predict the students' performance in elective subject. The aim of this research is to evaluate the students result in choosing the correct elective subjects. This research is focused on the ICT students who select DBM3033 as an elective subject. Two phases involved which are prepossessing data and mining data. RapidMiner software is used in mining data process. Classification technique is applied for decision tree method. The research findings showed that students whose result weak in both SPM Mathematics and DBM1033 are predicted as fail in final examination for DBM3033.","downloadable_attachments":[{"id":65204146,"asset_id":44722097,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":181511182,"first_name":"suhainy","last_name":"binti sulaiman","domain_name":"puo","page_name":"suhainybintisulaiman","display_name":"suhainy binti sulaiman","profile_url":"https://puo.academia.edu/suhainybintisulaiman?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":4095,"name":"Classification (Machine Learning)","url":"https://www.academia.edu/Documents/in/Classification_Machine_Learning_?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":162271,"name":"Decision Tree","url":"https://www.academia.edu/Documents/in/Decision_Tree?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_43695084" data-work_id="43695084" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/43695084/International_Conference_on_Data_Science_and_Applications_DSA_2020_">International Conference on Data Science and Applications (DSA 2020)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">International Conference on Data Science and Applications (DSA 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Science and Applications. It... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_43695084" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">International Conference on Data Science and Applications (DSA 2020) will act as a major<br />forum for the presentation of innovative ideas, approaches, developments, and research<br />projects in the areas of Data Science and Applications. It will also serve to facilitate the<br />exchange of information between researchers and industry professionals to discuss the latest<br />issues and advancement in the area of Data Science & Applications</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/43695084" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="3a582ac190c296e1725a173aac6da6bd" rel="nofollow" data-download="{"attachment_id":64778458,"asset_id":43695084,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/64778458/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="16715850" href="https://independent.academia.edu/IJDKPJOURNAL">International Journal of Data Mining & Knowledge Management Process ( IJDKP )</a><script data-card-contents-for-user="16715850" type="text/json">{"id":16715850,"first_name":"International Journal of Data Mining \u0026 Knowledge Management Process","last_name":"( IJDKP )","domain_name":"independent","page_name":"IJDKPJOURNAL","display_name":"International Journal of Data Mining \u0026 Knowledge Management Process ( IJDKP )","profile_url":"https://independent.academia.edu/IJDKPJOURNAL?f_ri=23995","photo":"https://0.academia-photos.com/16715850/4568261/39147186/s65_international_journal_of_data_mining_knowledge_management_process._ijdkp_.png"}</script></span></span></li><li class="js-paper-rank-work_43695084 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="43695084"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 43695084, container: ".js-paper-rank-work_43695084", }); 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$(".js-view-count[data-work-id=43695084]").text(description); $(".js-view-count-work_43695084").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_43695084").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="43695084"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="3419" href="https://www.academia.edu/Documents/in/Multimedia">Multimedia</a>, <script data-card-contents-for-ri="3419" type="text/json">{"id":3419,"name":"Multimedia","url":"https://www.academia.edu/Documents/in/Multimedia?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9351" href="https://www.academia.edu/Documents/in/Image_Analysis">Image Analysis</a>, <script data-card-contents-for-ri="9351" type="text/json">{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="10601" href="https://www.academia.edu/Documents/in/Data_Warehousing">Data Warehousing</a><script data-card-contents-for-ri="10601" type="text/json">{"id":10601,"name":"Data Warehousing","url":"https://www.academia.edu/Documents/in/Data_Warehousing?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=43695084]'), work: {"id":43695084,"title":"International Conference on Data Science and Applications (DSA 2020)","created_at":"2020-07-23T04:13:28.802-07:00","url":"https://www.academia.edu/43695084/International_Conference_on_Data_Science_and_Applications_DSA_2020_?f_ri=23995","dom_id":"work_43695084","summary":"International Conference on Data Science and Applications (DSA 2020) will act as a major\nforum for the presentation of innovative ideas, approaches, developments, and research\nprojects in the areas of Data Science and Applications. It will also serve to facilitate the\nexchange of information between researchers and industry professionals to discuss the latest\nissues and advancement in the area of Data Science \u0026 Applications","downloadable_attachments":[{"id":64778458,"asset_id":43695084,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":16715850,"first_name":"International Journal of Data Mining \u0026 Knowledge Management Process","last_name":"( IJDKP )","domain_name":"independent","page_name":"IJDKPJOURNAL","display_name":"International Journal of Data Mining \u0026 Knowledge Management Process ( IJDKP )","profile_url":"https://independent.academia.edu/IJDKPJOURNAL?f_ri=23995","photo":"https://0.academia-photos.com/16715850/4568261/39147186/s65_international_journal_of_data_mining_knowledge_management_process._ijdkp_.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":3419,"name":"Multimedia","url":"https://www.academia.edu/Documents/in/Multimedia?f_ri=23995","nofollow":false},{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=23995","nofollow":false},{"id":10601,"name":"Data Warehousing","url":"https://www.academia.edu/Documents/in/Data_Warehousing?f_ri=23995","nofollow":false},{"id":12512,"name":"Data Quality (Computer Science)","url":"https://www.academia.edu/Documents/in/Data_Quality_Computer_Science_?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":31774,"name":"Data sciences","url":"https://www.academia.edu/Documents/in/Data_sciences?f_ri=23995"},{"id":34344,"name":"Data mining (Data Analysis)","url":"https://www.academia.edu/Documents/in/Data_mining_Data_Analysis_?f_ri=23995"},{"id":39682,"name":"Graph Data Mining","url":"https://www.academia.edu/Documents/in/Graph_Data_Mining?f_ri=23995"},{"id":39693,"name":"Distributed Data Mining","url":"https://www.academia.edu/Documents/in/Distributed_Data_Mining?f_ri=23995"},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995"},{"id":69100,"name":"Data Science","url":"https://www.academia.edu/Documents/in/Data_Science?f_ri=23995"},{"id":86157,"name":"Graph Mining","url":"https://www.academia.edu/Documents/in/Graph_Mining?f_ri=23995"},{"id":99804,"name":"Privacy Preserving Data Mining","url":"https://www.academia.edu/Documents/in/Privacy_Preserving_Data_Mining?f_ri=23995"},{"id":106145,"name":"Classification","url":"https://www.academia.edu/Documents/in/Classification?f_ri=23995"},{"id":108488,"name":"Data Mining – Concepts and Techniques","url":"https://www.academia.edu/Documents/in/Data_Mining_Concepts_and_Techniques?f_ri=23995"},{"id":295755,"name":"Data Sciences for Complex Systems","url":"https://www.academia.edu/Documents/in/Data_Sciences_for_Complex_Systems?f_ri=23995"},{"id":319636,"name":"Data mining and Warehousing","url":"https://www.academia.edu/Documents/in/Data_mining_and_Warehousing?f_ri=23995"},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995"},{"id":3050442,"name":"Data Processing and Computer Science","url":"https://www.academia.edu/Documents/in/Data_Processing_and_Computer_Science?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18014823" data-work_id="18014823" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18014823/IT_INVESTMENT_EVALUATION_PRACTICE_USING_A_N_T_FOR_ANALYSIS_IN_MALAYSIAN_LOCAL_AUTHORITIES">IT INVESTMENT EVALUATION PRACTICE: USING A.N.T FOR ANALYSIS IN MALAYSIAN LOCAL AUTHORITIES.</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This research is to understand how evaluation is being used in managing IT investment. IT investment evaluation is an area to investigate mainly in the rise of computerized information system usage that rapidly growing with the support of... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_18014823" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This research is to understand how evaluation is being used in managing IT investment. IT investment evaluation is an area to investigate mainly in the rise of computerized information system usage that rapidly growing with the support of latest technology, customer’s demand and investment by the organization. In fact, it is not completely understood and valued by organization or government. In order to be competent, the evaluation should be assessed and justified. However, its implementation is hazy yet few organizations are aware of such evaluation implementation. Evaluation research is inadequate in public sectors and hardly reported especially in Malaysia. Actor Network Theory (ANT) is used to study the agents involved in IT evaluation practices and determine the influence of evaluation practices in local authority in Malaysia. In addition, this research will identify the impact of evaluation methodology employment towards the current issues from the ANT perspectives. This qualitative study approach was conducted in local authorities, focusing on pre and post evaluation of information system invested. ANT offered heterogeneity in describing and understanding the interrelationship of socio-technical aspect in IT investment evaluation analysis for Malaysian local authority. The findings revealed that lack of formal IT investment evaluation, low awareness level on the importance of evaluation, less exposure on the evaluation methodology and inappropriate appraisals of the proposed IT investment projects caused certain local authorities unable to deliver the benefits expected. With lack of formal IT evaluation, organization loses benefits and waste resources.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18014823" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="cddb117d28b762c4928198877c69df39" rel="nofollow" data-download="{"attachment_id":39828981,"asset_id":18014823,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39828981/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37945298" href="https://unikl.academia.edu/MukhlasA">Amalia Mukhlas</a><script data-card-contents-for-user="37945298" type="text/json">{"id":37945298,"first_name":"Amalia","last_name":"Mukhlas","domain_name":"unikl","page_name":"MukhlasA","display_name":"Amalia Mukhlas","profile_url":"https://unikl.academia.edu/MukhlasA?f_ri=23995","photo":"https://0.academia-photos.com/37945298/27401808/39022656/s65_amalia.mukhlas.jpg"}</script></span></span></li><li class="js-paper-rank-work_18014823 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="18014823"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 18014823, container: ".js-paper-rank-work_18014823", }); });</script></li><li class="js-percentile-work_18014823 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 18014823; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_18014823"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_18014823 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="18014823"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 18014823; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=18014823]").text(description); $(".js-view-count-work_18014823").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18014823").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18014823"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="52924" href="https://www.academia.edu/Documents/in/Mobile_Interface_Design">Mobile Interface Design</a>, <script data-card-contents-for-ri="52924" type="text/json">{"id":52924,"name":"Mobile Interface Design","url":"https://www.academia.edu/Documents/in/Mobile_Interface_Design?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="69604" href="https://www.academia.edu/Documents/in/Academic_Analytics">Academic Analytics</a>, <script data-card-contents-for-ri="69604" type="text/json">{"id":69604,"name":"Academic Analytics","url":"https://www.academia.edu/Documents/in/Academic_Analytics?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="100247" href="https://www.academia.edu/Documents/in/User_Interface_Design">User Interface Design</a><script data-card-contents-for-ri="100247" type="text/json">{"id":100247,"name":"User Interface Design","url":"https://www.academia.edu/Documents/in/User_Interface_Design?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18014823]'), work: {"id":18014823,"title":"IT INVESTMENT EVALUATION PRACTICE: USING A.N.T FOR ANALYSIS IN MALAYSIAN LOCAL AUTHORITIES.","created_at":"2015-11-09T05:48:32.298-08:00","url":"https://www.academia.edu/18014823/IT_INVESTMENT_EVALUATION_PRACTICE_USING_A_N_T_FOR_ANALYSIS_IN_MALAYSIAN_LOCAL_AUTHORITIES?f_ri=23995","dom_id":"work_18014823","summary":"This research is to understand how evaluation is being used in managing IT investment. IT investment evaluation is an area to investigate mainly in the rise of computerized information system usage that rapidly growing with the support of latest technology, customer’s demand and investment by the organization. In fact, it is not completely understood and valued by organization or government. In order to be competent, the evaluation should be assessed and justified. However, its implementation is hazy yet few organizations are aware of such evaluation implementation. Evaluation research is inadequate in public sectors and hardly reported especially in Malaysia. Actor Network Theory (ANT) is used to study the agents involved in IT evaluation practices and determine the influence of evaluation practices in local authority in Malaysia. In addition, this research will identify the impact of evaluation methodology employment towards the current issues from the ANT perspectives. This qualitative study approach was conducted in local authorities, focusing on pre and post evaluation of information system invested. ANT offered heterogeneity in describing and understanding the interrelationship of socio-technical aspect in IT investment evaluation analysis for Malaysian local authority. The findings revealed that lack of formal IT investment evaluation, low awareness level on the importance of evaluation, less exposure on the evaluation methodology and inappropriate appraisals of the proposed IT investment projects caused certain local authorities unable to deliver the benefits expected. With lack of formal IT evaluation, organization loses benefits and waste resources. ","downloadable_attachments":[{"id":39828981,"asset_id":18014823,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37945298,"first_name":"Amalia","last_name":"Mukhlas","domain_name":"unikl","page_name":"MukhlasA","display_name":"Amalia Mukhlas","profile_url":"https://unikl.academia.edu/MukhlasA?f_ri=23995","photo":"https://0.academia-photos.com/37945298/27401808/39022656/s65_amalia.mukhlas.jpg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":52924,"name":"Mobile Interface Design","url":"https://www.academia.edu/Documents/in/Mobile_Interface_Design?f_ri=23995","nofollow":false},{"id":69604,"name":"Academic Analytics","url":"https://www.academia.edu/Documents/in/Academic_Analytics?f_ri=23995","nofollow":false},{"id":100247,"name":"User Interface Design","url":"https://www.academia.edu/Documents/in/User_Interface_Design?f_ri=23995","nofollow":false},{"id":451644,"name":"IS/IT Strategy","url":"https://www.academia.edu/Documents/in/IS_IT_Strategy?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_12093699 coauthored" data-work_id="12093699" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/12093699/The_Process_of_Using_National_Education_Longitudinal_Datasets_in_School_Counseling_Research">The Process of Using National Education Longitudinal Datasets in School Counseling Research</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This article illuminates the process of using national longitudinal databases for school counseling research. We describe some of the more popular databases, their impact on policy, and some methodological considerations in preparing to... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_12093699" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This article illuminates the process of using national longitudinal databases for school counseling research. We describe some of the more popular databases, their impact on policy, and some methodological considerations in preparing to analyze the data. As an example, we use data from the Education Longitudinal Study 2002 (ELS) to examine predictors of student contact with school counselors for college information. Implications for counselor training and research are discussed. Suggestions for preparing school counseling doctoral students to use national education longitudinal databases are provided and potential themes for future research are outlined.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/12093699" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="fcbf558518568781ad316d8d21445d14" rel="nofollow" data-download="{"attachment_id":37411408,"asset_id":12093699,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/37411408/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="29954630" href="https://psu-us.academia.edu/JuliaBryan">Julia A Bryan</a><script data-card-contents-for-user="29954630" type="text/json">{"id":29954630,"first_name":"Julia","last_name":"Bryan","domain_name":"psu-us","page_name":"JuliaBryan","display_name":"Julia A Bryan","profile_url":"https://psu-us.academia.edu/JuliaBryan?f_ri=23995","photo":"https://0.academia-photos.com/29954630/8636354/31495089/s65_julia.bryan.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-12093699">+1</span><div class="hidden js-additional-users-12093699"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://johnshopkins.academia.edu/CherylHolcombMcCoy">Cheryl Holcomb-McCoy</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-12093699'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-12093699').html(); 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href="https://www.academia.edu/39625661/Decision_Support_for_an_Adversarial_Game_Environment_Using_Automatic_Hint_Generation">Decision Support for an Adversarial Game Environment Using Automatic Hint Generation</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The Hint Factory is a method of automatic hint generation that has been used to augment hints in a number of educational systems. Although the previous implementations were done in domains with largely deterministic environments, the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_39625661" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The Hint Factory is a method of automatic hint generation that has been used to augment hints in a number of educational systems. Although the previous implementations were done in domains with largely deterministic environments, the methods are inherently useful in stochastic environments with uncertainty. In this work, we explore the game Connect Four as a simple domain to give decision support under uncertainty. We speculate how the implementation created could be extended to other domains including simulated learning environments and advanced navigational tasks.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/39625661" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ca48f595784a3fa6d58d2690a44b9936" rel="nofollow" data-download="{"attachment_id":59783236,"asset_id":39625661,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/59783236/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="331840" href="https://cmu.academia.edu/JohnStamper">John Stamper</a><script data-card-contents-for-user="331840" type="text/json">{"id":331840,"first_name":"John","last_name":"Stamper","domain_name":"cmu","page_name":"JohnStamper","display_name":"John Stamper","profile_url":"https://cmu.academia.edu/JohnStamper?f_ri=23995","photo":"https://0.academia-photos.com/331840/138203/167166/s65_john.stamper.jpg"}</script></span></span></li><li class="js-paper-rank-work_39625661 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="39625661"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 39625661, container: ".js-paper-rank-work_39625661", }); 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We speculate how the implementation created could be extended to other domains including simulated learning environments and advanced navigational tasks.","downloadable_attachments":[{"id":59783236,"asset_id":39625661,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":331840,"first_name":"John","last_name":"Stamper","domain_name":"cmu","page_name":"JohnStamper","display_name":"John Stamper","profile_url":"https://cmu.academia.edu/JohnStamper?f_ri=23995","photo":"https://0.academia-photos.com/331840/138203/167166/s65_john.stamper.jpg"}],"research_interests":[{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=23995","nofollow":false},{"id":23232,"name":"Intelligent Tutoring Systems","url":"https://www.academia.edu/Documents/in/Intelligent_Tutoring_Systems?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_75235869" data-work_id="75235869" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/75235869/A_framework_for_childhood_obesity_classifications_and_predictions_using_NBtree">A framework for childhood obesity classifications and predictions using NBtree</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Obesity is a common issue nowadays. The numbers of obese people are increasing every year. There are evidences that childhood obesity persists into adulthood. Predicting obesity at an early age is both useful and important because... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_75235869" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Obesity is a common issue nowadays. The numbers of obese people are increasing every year. There are evidences that childhood obesity persists into adulthood. Predicting obesity at an early age is both useful and important because preventive ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/75235869" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="25428096c156f617dcfc6d30fb5073d9" rel="nofollow" data-download="{"attachment_id":83086818,"asset_id":75235869,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/83086818/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="128567631" href="https://independent.academia.edu/MuhamadHarizAdnan">Muhamad Hariz Adnan</a><script data-card-contents-for-user="128567631" type="text/json">{"id":128567631,"first_name":"Muhamad Hariz","last_name":"Adnan","domain_name":"independent","page_name":"MuhamadHarizAdnan","display_name":"Muhamad Hariz Adnan","profile_url":"https://independent.academia.edu/MuhamadHarizAdnan?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_75235869 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="75235869"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 75235869, container: ".js-paper-rank-work_75235869", }); 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Veri madenciliği terimi araştırmacılar tarafından farklı... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_39736761" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Son yıllarda Yapay Zeka ve Makine Öğrenmesi çalışmalarına artan ilgi, eğitim alanında yapılan  çalışmalarda da veri madenciliği ve öğrenme analitiklerinin ilerlemesini teşvik etti. Veri madenciliği terimi araştırmacılar tarafından farklı biçimlerde tanımlanmıştır. Baker (2004) veri madenciliğini makine öğreniminin, istatistiksel çalışmaların, farklı sınıflandırma algoritmaları kullanılarak büyük veri setlerinden yeni yönelimler ve kalıplar çıkarma işlemi olarak tanımlamaktadır. Veri madenciliği ayrıca büyük miktardaki veri setinden farklı ve potansiyel olarak faydalı bilgilerin keşfedilmesi olarak bilinen KDD’nin de  (knowledge discovery in database) bir alanıdır (Fayyad ve ark., 1996). Eğitim alanında yapılan veri madenciliği ise alanyazında Eğitsel Veri Madenciliği (EVM) olarak isimlendirilmektedir. EVM, veri olarak eğitime dair bilgileri sıklıkla çevrim içi kayıtlardan ve inceleme sonuçlarından elde edilen bilgileri kullanır. Bu bilgiler eğitsel kayıtlar, sınav sonuçları, bir uzaktan öğretim sisteminin kullanım bilgileri gibi bilgiler olabilirler. EVM bu bilgileri kullanarak varılacak kararların formülize edilmesi amacı güder. EVM teoriye yöneliktir ve pedagojik teoriyle bağlantıya odaklanır (Berland ve ark., 2014). Sosyal bilimlerde, halen, bilimsel topluluk tarafından geniş çapta kabul görebilecek bir teorik çerçeveyi desteklemeye yönelik çok az ampirik kanıt bulunmaktadır (Papamitsiou ve Economides, 2014). Gerçek dünyada, farklı öğrenme bağlamlarının büyüklüğü ve çeşitliği aslında EVM çalışmalarının da yönünü belirlemiştir. Öğrencilere, öğretmenlere ve okullara ait bilgiler çeşitlendikçe ve büyüdükçe EVM çalışmalarının da eğitim uygulamalarında kullanımı artmakta ve çalışmalar yoğunlaşmaktadır.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/39736761" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a72ff411eb569eb2237a5c9e328f0fde" rel="nofollow" data-download="{"attachment_id":59915656,"asset_id":39736761,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/59915656/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="6890730" href="https://bahcesehir.academia.edu/FatihCansu">Fatih K Cansu</a><script data-card-contents-for-user="6890730" type="text/json">{"id":6890730,"first_name":"Fatih","last_name":"Cansu","domain_name":"bahcesehir","page_name":"FatihCansu","display_name":"Fatih K Cansu","profile_url":"https://bahcesehir.academia.edu/FatihCansu?f_ri=23995","photo":"https://0.academia-photos.com/6890730/19016085/18963915/s65_fatih.cansu.jpg"}</script></span></span></li><li class="js-paper-rank-work_39736761 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="39736761"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 39736761, container: ".js-paper-rank-work_39736761", }); });</script></li><li class="js-percentile-work_39736761 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 39736761; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_39736761"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_39736761 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="39736761"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 39736761; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=39736761]").text(description); $(".js-view-count-work_39736761").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_39736761").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="39736761"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=39736761]'), work: {"id":39736761,"title":"Eğitsel Veri Madenciliğinin Önemi","created_at":"2019-07-02T13:30:36.296-07:00","url":"https://www.academia.edu/39736761/E%C4%9Fitsel_Veri_Madencili%C4%9Finin_%C3%96nemi?f_ri=23995","dom_id":"work_39736761","summary":"Son yıllarda Yapay Zeka ve Makine Öğrenmesi çalışmalarına artan ilgi, eğitim alanında yapılan çalışmalarda da veri madenciliği ve öğrenme analitiklerinin ilerlemesini teşvik etti. Veri madenciliği terimi araştırmacılar tarafından farklı biçimlerde tanımlanmıştır. Baker (2004) veri madenciliğini makine öğreniminin, istatistiksel çalışmaların, farklı sınıflandırma algoritmaları kullanılarak büyük veri setlerinden yeni yönelimler ve kalıplar çıkarma işlemi olarak tanımlamaktadır. Veri madenciliği ayrıca büyük miktardaki veri setinden farklı ve potansiyel olarak faydalı bilgilerin keşfedilmesi olarak bilinen KDD’nin de (knowledge discovery in database) bir alanıdır (Fayyad ve ark., 1996). Eğitim alanında yapılan veri madenciliği ise alanyazında Eğitsel Veri Madenciliği (EVM) olarak isimlendirilmektedir. EVM, veri olarak eğitime dair bilgileri sıklıkla çevrim içi kayıtlardan ve inceleme sonuçlarından elde edilen bilgileri kullanır. Bu bilgiler eğitsel kayıtlar, sınav sonuçları, bir uzaktan öğretim sisteminin kullanım bilgileri gibi bilgiler olabilirler. EVM bu bilgileri kullanarak varılacak kararların formülize edilmesi amacı güder. EVM teoriye yöneliktir ve pedagojik teoriyle bağlantıya odaklanır (Berland ve ark., 2014). Sosyal bilimlerde, halen, bilimsel topluluk tarafından geniş çapta kabul görebilecek bir teorik çerçeveyi desteklemeye yönelik çok az ampirik kanıt bulunmaktadır (Papamitsiou ve Economides, 2014). Gerçek dünyada, farklı öğrenme bağlamlarının büyüklüğü ve çeşitliği aslında EVM çalışmalarının da yönünü belirlemiştir. Öğrencilere, öğretmenlere ve okullara ait bilgiler çeşitlendikçe ve büyüdükçe EVM çalışmalarının da eğitim uygulamalarında kullanımı artmakta ve çalışmalar yoğunlaşmaktadır.","downloadable_attachments":[{"id":59915656,"asset_id":39736761,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":6890730,"first_name":"Fatih","last_name":"Cansu","domain_name":"bahcesehir","page_name":"FatihCansu","display_name":"Fatih K Cansu","profile_url":"https://bahcesehir.academia.edu/FatihCansu?f_ri=23995","photo":"https://0.academia-photos.com/6890730/19016085/18963915/s65_fatih.cansu.jpg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_853360" data-work_id="853360" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/853360/A_Learning_Design_Recommendation_System_Based_on_Markov_Decision_Processes">A Learning Design Recommendation System Based on Markov Decision Processes</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">As learning environments are gaining in features and in complexity, the e-learning industry is more and more interested in features easing teachers’ work. Learning design being a critical and time consuming task could be facilitated by... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_853360" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">As learning environments are gaining in features and in complexity, the e-learning industry is more and more interested in features easing teachers’ work. Learning design being a critical and time consuming task could be facilitated by intelligent components helping teachers build their learning activities. The Intelligent Learning Design Recommendation System (ILD-RS) is such a software component, designed to recommend learning paths during the learning design phase in a Learning Management System (LMS). Although ILD-RS exploits several parameters which are sometimes subject to controversy, such as learning styles and teaching styles, the main interest of the component lies on its algorithm based on Markov decision processes that takes into account the teacher’s use to refine its accuracy.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/853360" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="51ff7bd774ccd65efa2957cd8a9a8d11" rel="nofollow" data-download="{"attachment_id":30854054,"asset_id":853360,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/30854054/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="187420" href="https://nrc-ca.academia.edu/GuillaumeDurand">Guillaume Durand</a><script data-card-contents-for-user="187420" type="text/json">{"id":187420,"first_name":"Guillaume","last_name":"Durand","domain_name":"nrc-ca","page_name":"GuillaumeDurand","display_name":"Guillaume Durand","profile_url":"https://nrc-ca.academia.edu/GuillaumeDurand?f_ri=23995","photo":"https://0.academia-photos.com/187420/62995/69978/s65_guillaume.durand.jpg"}</script></span></span></li><li class="js-paper-rank-work_853360 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="853360"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 853360, container: ".js-paper-rank-work_853360", }); });</script></li><li class="js-percentile-work_853360 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 853360; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_853360"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_853360 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="853360"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 853360; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=853360]").text(description); $(".js-view-count-work_853360").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_853360").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="853360"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="7792" href="https://www.academia.edu/Documents/in/Learning_Design">Learning Design</a>, <script data-card-contents-for-ri="7792" type="text/json">{"id":7792,"name":"Learning Design","url":"https://www.academia.edu/Documents/in/Learning_Design?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=853360]'), work: {"id":853360,"title":"A Learning Design Recommendation System Based on Markov Decision Processes","created_at":"2011-08-22T23:38:30.509-07:00","url":"https://www.academia.edu/853360/A_Learning_Design_Recommendation_System_Based_on_Markov_Decision_Processes?f_ri=23995","dom_id":"work_853360","summary":"As learning environments are gaining in features and in complexity, the e-learning industry is more and more interested in features easing teachers’ work. Learning design being a critical and time consuming task could be facilitated by intelligent components helping teachers build their learning activities. The Intelligent Learning Design Recommendation System (ILD-RS) is such a software component, designed to recommend learning paths during the learning design phase in a Learning Management System (LMS). Although ILD-RS exploits several parameters which are sometimes subject to controversy, such as learning styles and teaching styles, the main interest of the component lies on its algorithm based on Markov decision processes that takes into account the teacher’s use to refine its accuracy.","downloadable_attachments":[{"id":30854054,"asset_id":853360,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":187420,"first_name":"Guillaume","last_name":"Durand","domain_name":"nrc-ca","page_name":"GuillaumeDurand","display_name":"Guillaume Durand","profile_url":"https://nrc-ca.academia.edu/GuillaumeDurand?f_ri=23995","photo":"https://0.academia-photos.com/187420/62995/69978/s65_guillaume.durand.jpg"}],"research_interests":[{"id":7792,"name":"Learning Design","url":"https://www.academia.edu/Documents/in/Learning_Design?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_38561952" data-work_id="38561952" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/38561952/Data_mining_approach_to_predicting_the_performance_of_first_year_student_in_a_university_using_the_admission_requirements">Data mining approach to predicting the performance of first year student in a university using the admission requirements</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The academic performance of a student in a university is determined by a number of factors, both academic and non-academic. Student that previously excelled at the secondary school level may lose focus due to peer pressure and social... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_38561952" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The academic performance of a student in a university is determined by a number of factors, both academic and non-academic. Student that previously excelled at the secondary school level may lose focus due to peer pressure and social lifestyle while those who previously struggled due to family distractions may be able to focus away from home, and as a result excel at the university. University admission in Nigeria is typically based on cognitive entry characteristics of a student which is mostly academic , and may not necessarily translate to excellence once in the university. In this study, the relationship between the cognitive admission entry requirements and the academic performance of students in their first year, using their CGPA and class of degree was examined using six data mining algorithms in KNIME and Orange platforms. Maximum accuracies of 50.23% and 51.9% respectively were observed, and the results were verified using regression models, with R2 values of 0.207 and 0.232 recorded which indicate that students' performance in their first year is not fully explained by cognitive entry requirements.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/38561952" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="85f9dde031ed6b2cc3bc9bb69d8c9f87" rel="nofollow" data-download="{"attachment_id":58634046,"asset_id":38561952,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/58634046/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="18681046" href="https://ibadan.academia.edu/AderibigbeAdekitan">Aderibigbe Adekitan</a><script data-card-contents-for-user="18681046" type="text/json">{"id":18681046,"first_name":"Aderibigbe","last_name":"Adekitan","domain_name":"ibadan","page_name":"AderibigbeAdekitan","display_name":"Aderibigbe Adekitan","profile_url":"https://ibadan.academia.edu/AderibigbeAdekitan?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_38561952 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="38561952"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 38561952, container: ".js-paper-rank-work_38561952", }); });</script></li><li class="js-percentile-work_38561952 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 38561952; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_38561952"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_38561952 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="38561952"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 38561952; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=38561952]").text(description); $(".js-view-count-work_38561952").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_38561952").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="38561952"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="5109" href="https://www.academia.edu/Documents/in/Pattern_Recognition">Pattern Recognition</a>, <script data-card-contents-for-ri="5109" type="text/json">{"id":5109,"name":"Pattern Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="14008" href="https://www.academia.edu/Documents/in/Knowledge_Discovery_in_Databases">Knowledge Discovery in Databases</a>, <script data-card-contents-for-ri="14008" type="text/json">{"id":14008,"name":"Knowledge Discovery in Databases","url":"https://www.academia.edu/Documents/in/Knowledge_Discovery_in_Databases?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=38561952]'), work: {"id":38561952,"title":"Data mining approach to predicting the performance of first year student in a university using the admission requirements","created_at":"2019-03-16T02:16:14.950-07:00","url":"https://www.academia.edu/38561952/Data_mining_approach_to_predicting_the_performance_of_first_year_student_in_a_university_using_the_admission_requirements?f_ri=23995","dom_id":"work_38561952","summary":"The academic performance of a student in a university is determined by a number of factors, both academic and non-academic. Student that previously excelled at the secondary school level may lose focus due to peer pressure and social lifestyle while those who previously struggled due to family distractions may be able to focus away from home, and as a result excel at the university. University admission in Nigeria is typically based on cognitive entry characteristics of a student which is mostly academic , and may not necessarily translate to excellence once in the university. In this study, the relationship between the cognitive admission entry requirements and the academic performance of students in their first year, using their CGPA and class of degree was examined using six data mining algorithms in KNIME and Orange platforms. Maximum accuracies of 50.23% and 51.9% respectively were observed, and the results were verified using regression models, with R2 values of 0.207 and 0.232 recorded which indicate that students' performance in their first year is not fully explained by cognitive entry requirements.","downloadable_attachments":[{"id":58634046,"asset_id":38561952,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":18681046,"first_name":"Aderibigbe","last_name":"Adekitan","domain_name":"ibadan","page_name":"AderibigbeAdekitan","display_name":"Aderibigbe Adekitan","profile_url":"https://ibadan.academia.edu/AderibigbeAdekitan?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":5109,"name":"Pattern Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=23995","nofollow":false},{"id":14008,"name":"Knowledge Discovery in Databases","url":"https://www.academia.edu/Documents/in/Knowledge_Discovery_in_Databases?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":30664,"name":"Pattern Recognition and Classification","url":"https://www.academia.edu/Documents/in/Pattern_Recognition_and_Classification?f_ri=23995"},{"id":34344,"name":"Data mining (Data Analysis)","url":"https://www.academia.edu/Documents/in/Data_mining_Data_Analysis_?f_ri=23995"},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995"},{"id":64642,"name":"Knowledge Discovery","url":"https://www.academia.edu/Documents/in/Knowledge_Discovery?f_ri=23995"},{"id":76424,"name":"Academic Performance","url":"https://www.academia.edu/Documents/in/Academic_Performance?f_ri=23995"},{"id":143038,"name":"Machine Learning and Pattern Recognition","url":"https://www.academia.edu/Documents/in/Machine_Learning_and_Pattern_Recognition?f_ri=23995"},{"id":254085,"name":"Data Mining and Knowledge Discovery","url":"https://www.academia.edu/Documents/in/Data_Mining_and_Knowledge_Discovery?f_ri=23995"},{"id":2047149,"name":"Nigerian university","url":"https://www.academia.edu/Documents/in/Nigerian_university?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_44089957" data-work_id="44089957" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/44089957/Gender_based_comparison_of_students_academic_performance_using_regression_models">Gender-based comparison of students' academic performance using regression models</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The process required to gain admission into tertiary institutions is challenging for Nigerian students. This is due to the various examinations and requirements that must be met to be qualified for admission among innumerable applicants.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_44089957" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The process required to gain admission into tertiary institutions is challenging for Nigerian students. This is due to the various examinations and requirements that must be met to be qualified for admission among innumerable applicants. It is therefore imperative that after admission, students must pursue academic excellence to justify the opportunity given to them, and this will also improve their chances of success after graduation. In a university, some first-year students struggle because of cultural disadvantages, as well as their economic and social backgrounds. This has resulted in poor performance by some students and inevitably led to bad grades at graduation and some drop out of the university without graduating. Female students are often said to perform a bit poorer in terms of academic performance. This study is a comparative performance analysis of male and female students in Science, Technology, Engineering and Mathematics (STEM), conducted using regression models. Trend analysis shows that in this case study, female students have a tendency to improve on their academic performance from their first to their final year. The highest R-squared value of 0.7069 was achieved based on a regression analysis of the performance of 1,093 female students.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/44089957" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a935b5d5507406bd48c33481002435f9" rel="nofollow" data-download="{"attachment_id":64436230,"asset_id":44089957,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/64436230/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="18681046" href="https://ibadan.academia.edu/AderibigbeAdekitan">Aderibigbe Adekitan</a><script data-card-contents-for-user="18681046" type="text/json">{"id":18681046,"first_name":"Aderibigbe","last_name":"Adekitan","domain_name":"ibadan","page_name":"AderibigbeAdekitan","display_name":"Aderibigbe Adekitan","profile_url":"https://ibadan.academia.edu/AderibigbeAdekitan?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_44089957 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="44089957"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 44089957, container: ".js-paper-rank-work_44089957", }); });</script></li><li class="js-percentile-work_44089957 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 44089957; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_44089957"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_44089957 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="44089957"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 44089957; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=44089957]").text(description); $(".js-view-count-work_44089957").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_44089957").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="44089957"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4205" href="https://www.academia.edu/Documents/in/Data_Analysis">Data Analysis</a>, <script data-card-contents-for-ri="4205" type="text/json">{"id":4205,"name":"Data Analysis","url":"https://www.academia.edu/Documents/in/Data_Analysis?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="14008" href="https://www.academia.edu/Documents/in/Knowledge_Discovery_in_Databases">Knowledge Discovery in Databases</a>, <script data-card-contents-for-ri="14008" type="text/json">{"id":14008,"name":"Knowledge Discovery in Databases","url":"https://www.academia.edu/Documents/in/Knowledge_Discovery_in_Databases?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=44089957]'), work: {"id":44089957,"title":"Gender-based comparison of students' academic performance using regression models","created_at":"2020-09-15T00:40:23.230-07:00","url":"https://www.academia.edu/44089957/Gender_based_comparison_of_students_academic_performance_using_regression_models?f_ri=23995","dom_id":"work_44089957","summary":"The process required to gain admission into tertiary institutions is challenging for Nigerian students. This is due to the various examinations and requirements that must be met to be qualified for admission among innumerable applicants. It is therefore imperative that after admission, students must pursue academic excellence to justify the opportunity given to them, and this will also improve their chances of success after graduation. In a university, some first-year students struggle because of cultural disadvantages, as well as their economic and social backgrounds. This has resulted in poor performance by some students and inevitably led to bad grades at graduation and some drop out of the university without graduating. Female students are often said to perform a bit poorer in terms of academic performance. This study is a comparative performance analysis of male and female students in Science, Technology, Engineering and Mathematics (STEM), conducted using regression models. Trend analysis shows that in this case study, female students have a tendency to improve on their academic performance from their first to their final year. The highest R-squared value of 0.7069 was achieved based on a regression analysis of the performance of 1,093 female students.","downloadable_attachments":[{"id":64436230,"asset_id":44089957,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":18681046,"first_name":"Aderibigbe","last_name":"Adekitan","domain_name":"ibadan","page_name":"AderibigbeAdekitan","display_name":"Aderibigbe Adekitan","profile_url":"https://ibadan.academia.edu/AderibigbeAdekitan?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":4205,"name":"Data Analysis","url":"https://www.academia.edu/Documents/in/Data_Analysis?f_ri=23995","nofollow":false},{"id":14008,"name":"Knowledge Discovery in Databases","url":"https://www.academia.edu/Documents/in/Knowledge_Discovery_in_Databases?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":34344,"name":"Data mining (Data Analysis)","url":"https://www.academia.edu/Documents/in/Data_mining_Data_Analysis_?f_ri=23995"},{"id":107672,"name":"Regression","url":"https://www.academia.edu/Documents/in/Regression?f_ri=23995"},{"id":123230,"name":"Regression Analysis","url":"https://www.academia.edu/Documents/in/Regression_Analysis?f_ri=23995"},{"id":199316,"name":"Multiple Linear Regression","url":"https://www.academia.edu/Documents/in/Multiple_Linear_Regression?f_ri=23995"},{"id":254085,"name":"Data Mining and Knowledge Discovery","url":"https://www.academia.edu/Documents/in/Data_Mining_and_Knowledge_Discovery?f_ri=23995"},{"id":403949,"name":"Teaching and Learning Strategies","url":"https://www.academia.edu/Documents/in/Teaching_and_Learning_Strategies?f_ri=23995"},{"id":2564997,"name":"Student Performance Prediction","url":"https://www.academia.edu/Documents/in/Student_Performance_Prediction?f_ri=23995"},{"id":3763258,"name":"Performance evaluation methodologies","url":"https://www.academia.edu/Documents/in/Performance_evaluation_methodologies?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_15510378" data-work_id="15510378" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/15510378/Detecting_sarcasm_from_students_feedback_in_Twitter">Detecting sarcasm from students' feedback in Twitter</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_15510378" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/15510378" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="333f92675362d8168490b2d8900bea12" rel="nofollow" data-download="{"attachment_id":38703091,"asset_id":15510378,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/38703091/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="31663136" href="https://port.academia.edu/MihaelaCocea">Mihaela Cocea</a><script data-card-contents-for-user="31663136" type="text/json">{"id":31663136,"first_name":"Mihaela","last_name":"Cocea","domain_name":"port","page_name":"MihaelaCocea","display_name":"Mihaela Cocea","profile_url":"https://port.academia.edu/MihaelaCocea?f_ri=23995","photo":"https://0.academia-photos.com/31663136/9470372/10552222/s65_mihaela.cocea.png"}</script></span></span></li><li class="js-paper-rank-work_15510378 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="15510378"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 15510378, container: ".js-paper-rank-work_15510378", }); });</script></li><li class="js-percentile-work_15510378 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 15510378; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_15510378"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_15510378 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="15510378"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 15510378; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=15510378]").text(description); $(".js-view-count-work_15510378").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_15510378").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="15510378"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="5379" href="https://www.academia.edu/Documents/in/Sentiment_Analysis">Sentiment Analysis</a>, <script data-card-contents-for-ri="5379" type="text/json">{"id":5379,"name":"Sentiment Analysis","url":"https://www.academia.edu/Documents/in/Sentiment_Analysis?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="5639" href="https://www.academia.edu/Documents/in/Text_Mining">Text Mining</a>, <script data-card-contents-for-ri="5639" type="text/json">{"id":5639,"name":"Text Mining","url":"https://www.academia.edu/Documents/in/Text_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=15510378]'), work: {"id":15510378,"title":"Detecting sarcasm from students' feedback in Twitter","created_at":"2015-09-08T07:31:14.293-07:00","url":"https://www.academia.edu/15510378/Detecting_sarcasm_from_students_feedback_in_Twitter?f_ri=23995","dom_id":"work_15510378","summary":"Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter. ","downloadable_attachments":[{"id":38703091,"asset_id":15510378,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":31663136,"first_name":"Mihaela","last_name":"Cocea","domain_name":"port","page_name":"MihaelaCocea","display_name":"Mihaela Cocea","profile_url":"https://port.academia.edu/MihaelaCocea?f_ri=23995","photo":"https://0.academia-photos.com/31663136/9470372/10552222/s65_mihaela.cocea.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":5379,"name":"Sentiment Analysis","url":"https://www.academia.edu/Documents/in/Sentiment_Analysis?f_ri=23995","nofollow":false},{"id":5639,"name":"Text Mining","url":"https://www.academia.edu/Documents/in/Text_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":1134456,"name":"Sarcasm Detection","url":"https://www.academia.edu/Documents/in/Sarcasm_Detection?f_ri=23995"},{"id":1179890,"name":"Students Feedback","url":"https://www.academia.edu/Documents/in/Students_Feedback?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_37781491" data-work_id="37781491" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/37781491/Reasons_for_Lower_Literacy_among_Girls_in_Himachal_Pradesh">Reasons for Lower Literacy among Girls in Himachal Pradesh</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Educational dropout is one of the major problems in India and for the whole world itself. This article presents the problem of girl's educational dropout of Himachal Pradesh in India. The literacy rate (LR) of the state is very excellent... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_37781491" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Educational dropout is one of the major problems in India and for the whole world itself. This article presents the problem of girl's educational dropout of Himachal Pradesh in India. The literacy rate (LR) of the state is very excellent up to 82.80%. But the discrepancy of male and female LR goes up to 13.60% and this discrepancy creates a foremost problem with the overall LR of this state. Work has been done to find out the reasons for the most minuscule LR of female as compared to male. So that some suggested measure can be taken to improve the LR of female in Himachal Pradesh.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/37781491" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="2dfc3d27b298f1bd35e45ff8faddacdc" rel="nofollow" data-download="{"attachment_id":57778179,"asset_id":37781491,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/57778179/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8037161" href="https://lovely-professional-university.academia.edu/MukeshKumar2">Dr Mukesh Kumar</a><script data-card-contents-for-user="8037161" type="text/json">{"id":8037161,"first_name":"Dr Mukesh","last_name":"Kumar","domain_name":"lovely-professional-university","page_name":"MukeshKumar2","display_name":"Dr Mukesh Kumar","profile_url":"https://lovely-professional-university.academia.edu/MukeshKumar2?f_ri=23995","photo":"https://0.academia-photos.com/8037161/3220392/93073688/s65_dr_mukesh.kumar.jpeg"}</script></span></span></li><li class="js-paper-rank-work_37781491 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="37781491"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 37781491, container: ".js-paper-rank-work_37781491", }); });</script></li><li class="js-percentile-work_37781491 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 37781491; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_37781491"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_37781491 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="37781491"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 37781491; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=37781491]").text(description); $(".js-view-count-work_37781491").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_37781491").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="37781491"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=37781491]'), work: {"id":37781491,"title":"Reasons for Lower Literacy among Girls in Himachal Pradesh","created_at":"2018-11-15T10:13:26.571-08:00","url":"https://www.academia.edu/37781491/Reasons_for_Lower_Literacy_among_Girls_in_Himachal_Pradesh?f_ri=23995","dom_id":"work_37781491","summary":"Educational dropout is one of the major problems in India and for the whole world itself. This article presents the problem of girl's educational dropout of Himachal Pradesh in India. The literacy rate (LR) of the state is very excellent up to 82.80%. But the discrepancy of male and female LR goes up to 13.60% and this discrepancy creates a foremost problem with the overall LR of this state. Work has been done to find out the reasons for the most minuscule LR of female as compared to male. So that some suggested measure can be taken to improve the LR of female in Himachal Pradesh.","downloadable_attachments":[{"id":57778179,"asset_id":37781491,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":8037161,"first_name":"Dr Mukesh","last_name":"Kumar","domain_name":"lovely-professional-university","page_name":"MukeshKumar2","display_name":"Dr Mukesh Kumar","profile_url":"https://lovely-professional-university.academia.edu/MukeshKumar2?f_ri=23995","photo":"https://0.academia-photos.com/8037161/3220392/93073688/s65_dr_mukesh.kumar.jpeg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_25905135" data-work_id="25905135" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25905135/Student_rules_Exploring_patterns_of_students_computer_efficacy_and_engagement_with_digital_technologies_in_learning">Student rules: Exploring patterns of students' computer- efficacy and engagement with digital technologies in learning</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Teachers' beliefs about students' engagement in and knowledge of digital technologies will affect technologically integrated learning designs. Over the past few decades, teachers have tended to feel that students were confident and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_25905135" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Teachers' beliefs about students' engagement in and knowledge of digital technologies will affect technologically integrated learning designs. Over the past few decades, teachers have tended to feel that students were confident and engaged users of digital technologies, but there is a growing body of research challenging this assumption. Given this disparity, it is necessary to examine students' confidence and engagement using digital technologies to understand how differences may affect experiences in technologically integrated learning. However, the complexity of teaching and learning can make it difficult to isolate and study multiple factors and their effects. This paper proposes the use of data mining techniques to examine unique patterns among key factors of students' technology use and experiences related to learning, as a way to inform teachers' practice and learning design. To do this, association rules mining and fuzzy representations are used to analyze a large student questionnaire dataset (N ¼ 8817). Results reveal substantially different patterns among school engagement and computer-efficacy factors between students with positive and negative engagement with digital technologies. Findings suggest implications for learning design and how teachers may attend to different experiences in technologically integrated learning and future research in this area.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25905135" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a77142038b55ca96fc354dc071586c7b" rel="nofollow" data-download="{"attachment_id":46269003,"asset_id":25905135,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46269003/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37715" href="https://uow.academia.edu/SarahHoward">Sarah K Howard</a><script data-card-contents-for-user="37715" type="text/json">{"id":37715,"first_name":"Sarah","last_name":"Howard","domain_name":"uow","page_name":"SarahHoward","display_name":"Sarah K Howard","profile_url":"https://uow.academia.edu/SarahHoward?f_ri=23995","photo":"https://0.academia-photos.com/37715/12520/92662592/s65_sarah.howard.jpg"}</script></span></span></li><li class="js-paper-rank-work_25905135 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="25905135"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 25905135, container: ".js-paper-rank-work_25905135", }); });</script></li><li class="js-percentile-work_25905135 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 25905135; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_25905135"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_25905135 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="25905135"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 25905135; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=25905135]").text(description); $(".js-view-count-work_25905135").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_25905135").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="25905135"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="7792" href="https://www.academia.edu/Documents/in/Learning_Design">Learning Design</a>, <script data-card-contents-for-ri="7792" type="text/json">{"id":7792,"name":"Learning Design","url":"https://www.academia.edu/Documents/in/Learning_Design?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="53426" href="https://www.academia.edu/Documents/in/Technology_Integration_in_Schools">Technology Integration in Schools</a>, <script data-card-contents-for-ri="53426" type="text/json">{"id":53426,"name":"Technology Integration in Schools","url":"https://www.academia.edu/Documents/in/Technology_Integration_in_Schools?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="54632" href="https://www.academia.edu/Documents/in/Classroom_Research">Classroom Research</a><script data-card-contents-for-ri="54632" type="text/json">{"id":54632,"name":"Classroom Research","url":"https://www.academia.edu/Documents/in/Classroom_Research?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=25905135]'), work: {"id":25905135,"title":"Student rules: Exploring patterns of students' computer- efficacy and engagement with digital technologies in learning","created_at":"2016-06-06T00:21:28.905-07:00","url":"https://www.academia.edu/25905135/Student_rules_Exploring_patterns_of_students_computer_efficacy_and_engagement_with_digital_technologies_in_learning?f_ri=23995","dom_id":"work_25905135","summary":"Teachers' beliefs about students' engagement in and knowledge of digital technologies will affect technologically integrated learning designs. Over the past few decades, teachers have tended to feel that students were confident and engaged users of digital technologies, but there is a growing body of research challenging this assumption. Given this disparity, it is necessary to examine students' confidence and engagement using digital technologies to understand how differences may affect experiences in technologically integrated learning. However, the complexity of teaching and learning can make it difficult to isolate and study multiple factors and their effects. This paper proposes the use of data mining techniques to examine unique patterns among key factors of students' technology use and experiences related to learning, as a way to inform teachers' practice and learning design. To do this, association rules mining and fuzzy representations are used to analyze a large student questionnaire dataset (N ¼ 8817). Results reveal substantially different patterns among school engagement and computer-efficacy factors between students with positive and negative engagement with digital technologies. Findings suggest implications for learning design and how teachers may attend to different experiences in technologically integrated learning and future research in this area.","downloadable_attachments":[{"id":46269003,"asset_id":25905135,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37715,"first_name":"Sarah","last_name":"Howard","domain_name":"uow","page_name":"SarahHoward","display_name":"Sarah K Howard","profile_url":"https://uow.academia.edu/SarahHoward?f_ri=23995","photo":"https://0.academia-photos.com/37715/12520/92662592/s65_sarah.howard.jpg"}],"research_interests":[{"id":7792,"name":"Learning Design","url":"https://www.academia.edu/Documents/in/Learning_Design?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":53426,"name":"Technology Integration in Schools","url":"https://www.academia.edu/Documents/in/Technology_Integration_in_Schools?f_ri=23995","nofollow":false},{"id":54632,"name":"Classroom Research","url":"https://www.academia.edu/Documents/in/Classroom_Research?f_ri=23995","nofollow":false},{"id":109865,"name":"Relationship of Computer Efficacy and Teaching and Research Skills in Higher Education","url":"https://www.academia.edu/Documents/in/Relationship_of_Computer_Efficacy_and_Teaching_and_Research_Skills_in_Higher_Education?f_ri=23995"},{"id":575493,"name":"Technology and Engagement","url":"https://www.academia.edu/Documents/in/Technology_and_Engagement?f_ri=23995"},{"id":1031372,"name":"Student Teacher Beliefs and Dilemmas","url":"https://www.academia.edu/Documents/in/Student_Teacher_Beliefs_and_Dilemmas?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_68660973" data-work_id="68660973" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/68660973/Mining_Frequent_Itemsets_using_Patricia_Tries">Mining Frequent Itemsets using Patricia Tries</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We present a depth-first algorithm, PatriciaMine, that discovers all frequent itemsets in a dataset, for a given support threshold. The algorithm is main-memory based and employs a Patricia trie to represent the dataset, which is space... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_68660973" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We present a depth-first algorithm, PatriciaMine, that discovers all frequent itemsets in a dataset, for a given support threshold. The algorithm is main-memory based and employs a Patricia trie to represent the dataset, which is space efficient for both dense and sparse datasets, whereas alternative representations were adopted by previous algorithms for these two cases. A number of optimizations have been introduced in the implementation of the algorithm. The paper reports several experimental results on real and artificial datasets, which assess the effectiveness of the implementation and show the better performance attained by PatriciaMine with respect to other prominent algorithms.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/68660973" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8c3953da6d7ce3e0d29a8f694df98e83" rel="nofollow" data-download="{"attachment_id":79065227,"asset_id":68660973,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/79065227/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="7292611" href="https://independent.academia.edu/DarioZandolin">Dario Zandolin</a><script data-card-contents-for-user="7292611" type="text/json">{"id":7292611,"first_name":"Dario","last_name":"Zandolin","domain_name":"independent","page_name":"DarioZandolin","display_name":"Dario Zandolin","profile_url":"https://independent.academia.edu/DarioZandolin?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_68660973 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="68660973"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 68660973, container: ".js-paper-rank-work_68660973", }); 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$(".js-view-count[data-work-id=68660973]").text(description); $(".js-view-count-work_68660973").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_68660973").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="68660973"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="55073" href="https://www.academia.edu/Documents/in/Frequent_Itemset_Mining">Frequent Itemset Mining</a><script data-card-contents-for-ri="55073" type="text/json">{"id":55073,"name":"Frequent Itemset Mining","url":"https://www.academia.edu/Documents/in/Frequent_Itemset_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=68660973]'), work: {"id":68660973,"title":"Mining Frequent Itemsets using Patricia Tries","created_at":"2022-01-19T00:49:51.273-08:00","url":"https://www.academia.edu/68660973/Mining_Frequent_Itemsets_using_Patricia_Tries?f_ri=23995","dom_id":"work_68660973","summary":"We present a depth-first algorithm, PatriciaMine, that discovers all frequent itemsets in a dataset, for a given support threshold. The algorithm is main-memory based and employs a Patricia trie to represent the dataset, which is space efficient for both dense and sparse datasets, whereas alternative representations were adopted by previous algorithms for these two cases. A number of optimizations have been introduced in the implementation of the algorithm. The paper reports several experimental results on real and artificial datasets, which assess the effectiveness of the implementation and show the better performance attained by PatriciaMine with respect to other prominent algorithms.","downloadable_attachments":[{"id":79065227,"asset_id":68660973,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":7292611,"first_name":"Dario","last_name":"Zandolin","domain_name":"independent","page_name":"DarioZandolin","display_name":"Dario Zandolin","profile_url":"https://independent.academia.edu/DarioZandolin?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":55073,"name":"Frequent Itemset Mining","url":"https://www.academia.edu/Documents/in/Frequent_Itemset_Mining?f_ri=23995","nofollow":false},{"id":94537,"name":"Datamining","url":"https://www.academia.edu/Documents/in/Datamining?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_35838815" data-work_id="35838815" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/35838815/A_SURVEY_OF_BIG_DATA_ANALYTICS">A SURVEY OF BIG DATA ANALYTICS</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Due to the arrival of new technologies, devices, and communication means, the amount of data produced by mankind is growing rapidly every year. This gives rise to the era of big data. The term big data comes with the new challenges to... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_35838815" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Due to the arrival of new technologies, devices, and communication means, the amount of data produced by mankind is growing rapidly every year. This gives rise to the era of big data. The term big data comes with the new challenges to input, process and output the data. The paper focuses on limitation of traditional approach to manage the data and the components that are useful in handling big data. One of the approaches used in processing big data is Hadoop framework, the paper presents the major components of the framework and working process within the framework.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/35838815" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8562eac2811b79f970900953fac8450e" rel="nofollow" data-download="{"attachment_id":55716957,"asset_id":35838815,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/55716957/download_file?st=MTczMjM5MDYwMSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="74068792" href="https://independent.academia.edu/Journal_IJIST">International Journal of Information Sciences and Techniques (IJIST)</a><script data-card-contents-for-user="74068792" type="text/json">{"id":74068792,"first_name":"International Journal of Information Sciences and Techniques","last_name":"(IJIST)","domain_name":"independent","page_name":"Journal_IJIST","display_name":"International Journal of Information Sciences and Techniques (IJIST)","profile_url":"https://independent.academia.edu/Journal_IJIST?f_ri=23995","photo":"https://0.academia-photos.com/74068792/18783181/111422471/s65_international_journal_of_information_sciences_and_techniques._ijist_.png"}</script></span></span></li><li class="js-paper-rank-work_35838815 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="35838815"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 35838815, container: ".js-paper-rank-work_35838815", }); 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$(".js-view-count[data-work-id=35838815]").text(description); $(".js-view-count-work_35838815").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_35838815").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="35838815"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">28</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="965" href="https://www.academia.edu/Documents/in/Formal_Concept_Analysis_Data_Mining_">Formal Concept Analysis (Data Mining)</a>, <script data-card-contents-for-ri="965" type="text/json">{"id":965,"name":"Formal Concept Analysis (Data Mining)","url":"https://www.academia.edu/Documents/in/Formal_Concept_Analysis_Data_Mining_?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2482" href="https://www.academia.edu/Documents/in/Database_Systems">Database Systems</a><script data-card-contents-for-ri="2482" type="text/json">{"id":2482,"name":"Database Systems","url":"https://www.academia.edu/Documents/in/Database_Systems?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=35838815]'), work: {"id":35838815,"title":"A SURVEY OF BIG DATA ANALYTICS","created_at":"2018-02-04T22:12:52.342-08:00","url":"https://www.academia.edu/35838815/A_SURVEY_OF_BIG_DATA_ANALYTICS?f_ri=23995","dom_id":"work_35838815","summary":"Due to the arrival of new technologies, devices, and communication means, the amount of data produced by mankind is growing rapidly every year. This gives rise to the era of big data. The term big data comes with the new challenges to input, process and output the data. The paper focuses on limitation of traditional approach to manage the data and the components that are useful in handling big data. One of the approaches used in processing big data is Hadoop framework, the paper presents the major components of the framework and working process within the framework.","downloadable_attachments":[{"id":55716957,"asset_id":35838815,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":74068792,"first_name":"International Journal of Information Sciences and Techniques","last_name":"(IJIST)","domain_name":"independent","page_name":"Journal_IJIST","display_name":"International Journal of Information Sciences and Techniques (IJIST)","profile_url":"https://independent.academia.edu/Journal_IJIST?f_ri=23995","photo":"https://0.academia-photos.com/74068792/18783181/111422471/s65_international_journal_of_information_sciences_and_techniques._ijist_.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false},{"id":965,"name":"Formal Concept Analysis (Data Mining)","url":"https://www.academia.edu/Documents/in/Formal_Concept_Analysis_Data_Mining_?f_ri=23995","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":2482,"name":"Database Systems","url":"https://www.academia.edu/Documents/in/Database_Systems?f_ri=23995","nofollow":false},{"id":7960,"name":"Temporal Data Mining","url":"https://www.academia.edu/Documents/in/Temporal_Data_Mining?f_ri=23995"},{"id":9447,"name":"Stream Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Stream_Mining_Data_Mining_?f_ri=23995"},{"id":14494,"name":"Opinion Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Opinion_Mining_Data_Mining_?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":27360,"name":"Databases","url":"https://www.academia.edu/Documents/in/Databases?f_ri=23995"},{"id":32008,"name":"Data mining in Decision Support Systems","url":"https://www.academia.edu/Documents/in/Data_mining_in_Decision_Support_Systems?f_ri=23995"},{"id":32701,"name":"Data Mining in Bioinformatics","url":"https://www.academia.edu/Documents/in/Data_Mining_in_Bioinformatics?f_ri=23995"},{"id":34344,"name":"Data mining (Data Analysis)","url":"https://www.academia.edu/Documents/in/Data_mining_Data_Analysis_?f_ri=23995"},{"id":39682,"name":"Graph Data Mining","url":"https://www.academia.edu/Documents/in/Graph_Data_Mining?f_ri=23995"},{"id":39693,"name":"Distributed Data Mining","url":"https://www.academia.edu/Documents/in/Distributed_Data_Mining?f_ri=23995"},{"id":99804,"name":"Privacy Preserving Data Mining","url":"https://www.academia.edu/Documents/in/Privacy_Preserving_Data_Mining?f_ri=23995"},{"id":108488,"name":"Data Mining – Concepts and Techniques","url":"https://www.academia.edu/Documents/in/Data_Mining_Concepts_and_Techniques?f_ri=23995"},{"id":167122,"name":"Health Care Informatics, Health Data Analytics","url":"https://www.academia.edu/Documents/in/Health_Care_Informatics_Health_Data_Analytics?f_ri=23995"},{"id":394230,"name":"Current Trends in Data Mining","url":"https://www.academia.edu/Documents/in/Current_Trends_in_Data_Mining?f_ri=23995"},{"id":460675,"name":"Data Mining Techniques","url":"https://www.academia.edu/Documents/in/Data_Mining_Techniques?f_ri=23995"},{"id":633426,"name":"Social Media Data Analytics","url":"https://www.academia.edu/Documents/in/Social_Media_Data_Analytics?f_ri=23995"},{"id":994859,"name":"Data Mining and Business Intelligence","url":"https://www.academia.edu/Documents/in/Data_Mining_and_Business_Intelligence?f_ri=23995"},{"id":1003611,"name":"Business Analytics; Data Mining; Statistical Learning","url":"https://www.academia.edu/Documents/in/Business_Analytics_Data_Mining_Statistical_Learning?f_ri=23995"},{"id":1631158,"name":"Financial Data Analytics","url":"https://www.academia.edu/Documents/in/Financial_Data_Analytics?f_ri=23995"},{"id":1742173,"name":"data mining and Big data analytics in science and engineering","url":"https://www.academia.edu/Documents/in/data_mining_and_Big_data_analytics_in_science_and_engineering?f_ri=23995"},{"id":1760477,"name":"Data and Analytics","url":"https://www.academia.edu/Documents/in/Data_and_Analytics?f_ri=23995"},{"id":1775749,"name":"Marketing Analytics and Big Data","url":"https://www.academia.edu/Documents/in/Marketing_Analytics_and_Big_Data?f_ri=23995"},{"id":2531766,"name":"Cybersecurity Data Analytics","url":"https://www.academia.edu/Documents/in/Cybersecurity_Data_Analytics?f_ri=23995"},{"id":2884809,"name":"Hadoop Framework","url":"https://www.academia.edu/Documents/in/Hadoop_Framework?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_38241914" data-work_id="38241914" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/38241914/TOP_DOWNLOADED_PAPERS_International_Journal_of_Computer_Aided_technologies_IJCAx_">TOP DOWNLOADED PAPERS - International Journal of Computer-Aided technologies (IJCAx)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Computer-aided technologies (CAx) mean the use of computer technology to aid in the design, analysis and manufacture various products. International Journal of Computer-Aided technologies (IJCAx) is an open access, peer-reviewed journal... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_38241914" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Computer-aided technologies (CAx) mean the use of computer technology to aid in the design, analysis and manufacture various products. International Journal of Computer-Aided technologies (IJCAx)  is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Aided technologies such as CAD, CAM, CAIM,CAR, CARD, CASE etc. The journal focuses on all technical and practical aspects of Computer Aided technologies. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced CAx tools and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in all Computer Aided technologies</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/38241914" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="562a5d5f76183ad34af97f6893adbed7" rel="nofollow" data-download="{"attachment_id":58283596,"asset_id":38241914,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/58283596/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="86974900" href="https://independent.academia.edu/InternationalJournalofComputerAidedtechnologiesIJCAx">International Journal of Computer-Aided technologies (IJCAx)</a><script data-card-contents-for-user="86974900" type="text/json">{"id":86974900,"first_name":"International Journal of Computer-Aided technologies","last_name":"(IJCAx)","domain_name":"independent","page_name":"InternationalJournalofComputerAidedtechnologiesIJCAx","display_name":"International Journal of Computer-Aided technologies (IJCAx)","profile_url":"https://independent.academia.edu/InternationalJournalofComputerAidedtechnologiesIJCAx?f_ri=23995","photo":"https://0.academia-photos.com/86974900/20109798/74507170/s65_international_journal_of_computer-aided_technologies._ijcax_.jpg"}</script></span></span></li><li class="js-paper-rank-work_38241914 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="38241914"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 38241914, container: ".js-paper-rank-work_38241914", }); 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type="text/json">{"id":1681,"name":"Decision Making","url":"https://www.academia.edu/Documents/in/Decision_Making?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=81182172]'), work: 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class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">"Elinizdeki bu kitap, sosyal psikolojinin konularını en geniş kapsamıyla ele almakta, klasikleşmiş deneysel ve saha araştırmalarını en güncel bilimsel çalışmalarla harmanlamaktadır. Bu bakımdan, akademisyen ve öğrencilerin... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_16546144" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">"Elinizdeki bu kitap, sosyal psikolojinin konularını en geniş kapsamıyla ele almakta, klasikleşmiş deneysel ve saha araştırmalarını en güncel bilimsel çalışmalarla harmanlamaktadır. Bu bakımdan, akademisyen ve öğrencilerin yararlanabileceği eşsiz bir kaynaktır. Kitapta, sosyal psikoloji konuları bölüm bölüm ele alınmıştır; ilgili kavram, terim, kuram ve araştırmalar aktarılırken her bölüm kendi içinde bir bütünlük arz edecek şekilde akıcı bir öyküsel kurguyla ve dille yazılmıştır ayrıca bu kitap; tarihsel olaylarla, edebî ve felsefi metaforlarla zenginleştirilmiştir. <br />Ayrıca bu kapsamlı çalışma, sadece bilimsel bir disiplinin temel konularını okuyucuya aktarmakla kalmamakta, aynı zamanda savaş, açlık, çevre gibi gerçek dünya sorunlarının sosyal psikolojik boyutlarıyla ilgili çözüm önerileri de getirmektedir. Bu bakımdan elinizdeki kitap yalnızca bir ders kitabı değil, aynı zamanda sosyal psikolojiye ilgi duyan herkesin merakla okuyabileceği bir kitaptır."</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/16546144" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5350040" href="https://istanbulc.academia.edu/GamzeSart">Gamze Sart</a><script data-card-contents-for-user="5350040" type="text/json">{"id":5350040,"first_name":"Gamze","last_name":"Sart","domain_name":"istanbulc","page_name":"GamzeSart","display_name":"Gamze Sart","profile_url":"https://istanbulc.academia.edu/GamzeSart?f_ri=23995","photo":"https://0.academia-photos.com/5350040/3697412/4333558/s65_gamze.sart.jpg"}</script></span></span></li><li class="js-paper-rank-work_16546144 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="16546144"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 16546144, container: ".js-paper-rank-work_16546144", }); 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Bu bakımdan, akademisyen ve öğrencilerin yararlanabileceği eşsiz bir kaynaktır. Kitapta, sosyal psikoloji konuları bölüm bölüm ele alınmıştır; ilgili kavram, terim, kuram ve araştırmalar aktarılırken her bölüm kendi içinde bir bütünlük arz edecek şekilde akıcı bir öyküsel kurguyla ve dille yazılmıştır ayrıca bu kitap; tarihsel olaylarla, edebî ve felsefi metaforlarla zenginleştirilmiştir. \nAyrıca bu kapsamlı çalışma, sadece bilimsel bir disiplinin temel konularını okuyucuya aktarmakla kalmamakta, aynı zamanda savaş, açlık, çevre gibi gerçek dünya sorunlarının sosyal psikolojik boyutlarıyla ilgili çözüm önerileri de getirmektedir. Bu bakımdan elinizdeki kitap yalnızca bir ders kitabı değil, aynı zamanda sosyal psikolojiye ilgi duyan herkesin merakla okuyabileceği bir kitaptır.\" ","downloadable_attachments":[],"ordered_authors":[{"id":5350040,"first_name":"Gamze","last_name":"Sart","domain_name":"istanbulc","page_name":"GamzeSart","display_name":"Gamze Sart","profile_url":"https://istanbulc.academia.edu/GamzeSart?f_ri=23995","photo":"https://0.academia-photos.com/5350040/3697412/4333558/s65_gamze.sart.jpg"}],"research_interests":[{"id":27,"name":"Entrepreneurship","url":"https://www.academia.edu/Documents/in/Entrepreneurship?f_ri=23995","nofollow":false},{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=23995","nofollow":false},{"id":226,"name":"Clinical Psychology","url":"https://www.academia.edu/Documents/in/Clinical_Psychology?f_ri=23995","nofollow":false},{"id":227,"name":"Psychological 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significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_43855091" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/43855091" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f0e1ae1ae14b94d9bfd63fed53d0b055" rel="nofollow" data-download="{"attachment_id":64178374,"asset_id":43855091,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/64178374/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="16715850" href="https://independent.academia.edu/IJDKPJOURNAL">International Journal of Data Mining & Knowledge Management Process ( IJDKP )</a><script data-card-contents-for-user="16715850" type="text/json">{"id":16715850,"first_name":"International Journal of Data Mining \u0026 Knowledge Management Process","last_name":"( IJDKP )","domain_name":"independent","page_name":"IJDKPJOURNAL","display_name":"International Journal of Data Mining \u0026 Knowledge Management Process ( IJDKP )","profile_url":"https://independent.academia.edu/IJDKPJOURNAL?f_ri=23995","photo":"https://0.academia-photos.com/16715850/4568261/39147186/s65_international_journal_of_data_mining_knowledge_management_process._ijdkp_.png"}</script></span></span></li><li class="js-paper-rank-work_43855091 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="43855091"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 43855091, container: ".js-paper-rank-work_43855091", }); 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Due to sudden rising of various educational institutions all around the world most of the institutions are trying hard to... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_24311300" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">— In the present days, education plays a vital role to stimulate the people to lead their life more comfortable. Due to sudden rising of various educational institutions all around the world most of the institutions are trying hard to survive. Institutions offering specially higher education are striving hard to maintain the quality offered to the students. There are lots of factors are influencing the quality of education institutions like Infrastructure, Teaching and learning methods, Laboratories, Campus Placements, Linkages with Industries etc. One among the major factor which influences the quality of an institution is the student feedback. Now a days institutions are paying more attention towards the student feedback on their experience with their lecturers on the quality of delivery of course content's in Classroom. Retention of institutions with a good numbers is dependent on the understanding and</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/24311300" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="5625562f19200a930fd059b75c6f8047" rel="nofollow" data-download="{"attachment_id":44648345,"asset_id":24311300,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/44648345/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8659111" href="https://bluecrestcollege.academia.edu/SujithJayaprakash">Sujith Jayaprakash</a><script data-card-contents-for-user="8659111" type="text/json">{"id":8659111,"first_name":"Sujith","last_name":"Jayaprakash","domain_name":"bluecrestcollege","page_name":"SujithJayaprakash","display_name":"Sujith Jayaprakash","profile_url":"https://bluecrestcollege.academia.edu/SujithJayaprakash?f_ri=23995","photo":"https://0.academia-photos.com/8659111/2904056/13784865/s65_sujith.jayaprakash.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-24311300">+1</span><div class="hidden js-additional-users-24311300"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://bluecrestcollege.academia.edu/DrBala">Balamurugan Easwaran</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-24311300'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-24311300').html(); 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Gilay C Shamika</a><script data-card-contents-for-user="31988675" type="text/json">{"id":31988675,"first_name":"Eng. Gilay","last_name":"Shamika","domain_name":"udsm","page_name":"EngGilayShamika","display_name":"Eng. Gilay C Shamika","profile_url":"https://udsm.academia.edu/EngGilayShamika?f_ri=23995","photo":"https://0.academia-photos.com/31988675/9527968/10618987/s65_gilay.shamika.jpg"}</script></span></span></li><li class="js-paper-rank-work_12866388 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="12866388"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 12866388, container: ".js-paper-rank-work_12866388", }); });</script></li><li class="js-percentile-work_12866388 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 12866388; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_12866388"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_12866388 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="12866388"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 12866388; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=12866388]").text(description); $(".js-view-count-work_12866388").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_12866388").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="12866388"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="13297" href="https://www.academia.edu/Documents/in/Cognitive_Linguistics">Cognitive Linguistics</a>, <script data-card-contents-for-ri="13297" type="text/json">{"id":13297,"name":"Cognitive Linguistics","url":"https://www.academia.edu/Documents/in/Cognitive_Linguistics?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=12866388]'), work: {"id":12866388,"title":"GUIDE HAND BOOK ON FANCY TANZANITE By Shamika","created_at":"2015-06-08T07:46:39.920-07:00","url":"https://www.academia.edu/12866388/GUIDE_HAND_BOOK_ON_FANCY_TANZANITE_By_Shamika?f_ri=23995","dom_id":"work_12866388","summary":null,"downloadable_attachments":[{"id":37856340,"asset_id":12866388,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":31988675,"first_name":"Eng. Gilay","last_name":"Shamika","domain_name":"udsm","page_name":"EngGilayShamika","display_name":"Eng. Gilay C Shamika","profile_url":"https://udsm.academia.edu/EngGilayShamika?f_ri=23995","photo":"https://0.academia-photos.com/31988675/9527968/10618987/s65_gilay.shamika.jpg"}],"research_interests":[{"id":13297,"name":"Cognitive Linguistics","url":"https://www.academia.edu/Documents/in/Cognitive_Linguistics?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_75616348" data-work_id="75616348" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/75616348/Call_for_Papers_7th_International_Conference_on_Data_Mining_and_Knowledge_Management_DaKM_2022_">Call for Papers - 7th International Conference on Data Mining & Knowledge Management (DaKM 2022)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">7th International Conference on Data Mining & Knowledge Management (DaKM 2022) provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum. Authors are solicited to contribute to the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_75616348" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">7th International Conference on Data Mining & Knowledge Management (DaKM 2022) provides<br />a forum for researchers who address this issue and to present their work in a peer-reviewed forum.<br />Authors are solicited to contribute to the conference by submitting articles that illustrate research<br />results, projects, surveying works and industrial experiences that describe significant advances in the<br />following areas, but are not limited to these topics only.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/75616348" 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class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="21252910" href="https://independent.academia.edu/ACIJJournal">Advanced Computing: An International Journal ( ACIJ )</a><script data-card-contents-for-user="21252910" type="text/json">{"id":21252910,"first_name":"Advanced Computing: An International Journal","last_name":"( ACIJ )","domain_name":"independent","page_name":"ACIJJournal","display_name":"Advanced Computing: An International Journal ( ACIJ )","profile_url":"https://independent.academia.edu/ACIJJournal?f_ri=23995","photo":"https://0.academia-photos.com/21252910/5871420/60189180/s65_advanced_computing_an_international_journal._acij_.jpg"}</script></span></span></li><li class="js-paper-rank-work_75616348 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="75616348"><i class="u-m1x fa 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view-count u-mr2x" data-work-id="75616348"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75616348; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75616348]").text(description); $(".js-view-count-work_75616348").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_75616348").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="75616348"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="442" href="https://www.academia.edu/Documents/in/Parallel_Computing">Parallel Computing</a>, <script data-card-contents-for-ri="442" type="text/json">{"id":442,"name":"Parallel Computing","url":"https://www.academia.edu/Documents/in/Parallel_Computing?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9351" href="https://www.academia.edu/Documents/in/Image_Analysis">Image Analysis</a>, <script data-card-contents-for-ri="9351" type="text/json">{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="14494" href="https://www.academia.edu/Documents/in/Opinion_Mining_Data_Mining_">Opinion Mining (Data Mining)</a><script data-card-contents-for-ri="14494" type="text/json">{"id":14494,"name":"Opinion Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Opinion_Mining_Data_Mining_?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=75616348]'), work: {"id":75616348,"title":"Call for Papers - 7th International Conference on Data Mining \u0026 Knowledge Management (DaKM 2022)","created_at":"2022-04-06T03:57:44.592-07:00","url":"https://www.academia.edu/75616348/Call_for_Papers_7th_International_Conference_on_Data_Mining_and_Knowledge_Management_DaKM_2022_?f_ri=23995","dom_id":"work_75616348","summary":"7th International Conference on Data Mining \u0026 Knowledge Management (DaKM 2022) provides\na forum for researchers who address this issue and to present their work in a peer-reviewed forum.\nAuthors are solicited to contribute to the conference by submitting articles that illustrate research\nresults, projects, surveying works and industrial experiences that describe significant advances in the\nfollowing areas, but are not limited to these topics only.","downloadable_attachments":[{"id":88208270,"asset_id":75616348,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":21252910,"first_name":"Advanced Computing: An International Journal","last_name":"( ACIJ )","domain_name":"independent","page_name":"ACIJJournal","display_name":"Advanced Computing: An International Journal ( ACIJ )","profile_url":"https://independent.academia.edu/ACIJJournal?f_ri=23995","photo":"https://0.academia-photos.com/21252910/5871420/60189180/s65_advanced_computing_an_international_journal._acij_.jpg"}],"research_interests":[{"id":442,"name":"Parallel 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Analysis)","url":"https://www.academia.edu/Documents/in/Data_mining_Data_Analysis_?f_ri=23995"},{"id":39693,"name":"Distributed Data Mining","url":"https://www.academia.edu/Documents/in/Distributed_Data_Mining?f_ri=23995"},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995"},{"id":93179,"name":"Data Stream Mining","url":"https://www.academia.edu/Documents/in/Data_Stream_Mining?f_ri=23995"},{"id":99804,"name":"Privacy Preserving Data Mining","url":"https://www.academia.edu/Documents/in/Privacy_Preserving_Data_Mining?f_ri=23995"},{"id":108488,"name":"Data Mining – Concepts and Techniques","url":"https://www.academia.edu/Documents/in/Data_Mining_Concepts_and_Techniques?f_ri=23995"},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995"},{"id":460675,"name":"Data Mining Techniques","url":"https://www.academia.edu/Documents/in/Data_Mining_Techniques?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_1481096" data-work_id="1481096" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/1481096/Data_Mining_A_Prediction_for_Performance_Improvement_of_Engineering_Students_using_Classification">Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/1481096" 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class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="340707" href="https://vbspu.academia.edu/SaurabhPal">Saurabh Pal</a><script data-card-contents-for-user="340707" type="text/json">{"id":340707,"first_name":"Saurabh","last_name":"Pal","domain_name":"vbspu","page_name":"SaurabhPal","display_name":"Saurabh Pal","profile_url":"https://vbspu.academia.edu/SaurabhPal?f_ri=23995","photo":"https://0.academia-photos.com/340707/737364/1489470/s65_saurabh.pal.jpg"}</script></span></span></li><li class="js-paper-rank-work_1481096 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="1481096"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 1481096, container: ".js-paper-rank-work_1481096", }); });</script></li><li 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description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=1481096]").text(description); $(".js-view-count-work_1481096").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_1481096").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="1481096"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=1481096]'), work: {"id":1481096,"title":"Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification","created_at":"2012-03-21T21:07:44.583-07:00","url":"https://www.academia.edu/1481096/Data_Mining_A_Prediction_for_Performance_Improvement_of_Engineering_Students_using_Classification?f_ri=23995","dom_id":"work_1481096","summary":null,"downloadable_attachments":[{"id":31151407,"asset_id":1481096,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":340707,"first_name":"Saurabh","last_name":"Pal","domain_name":"vbspu","page_name":"SaurabhPal","display_name":"Saurabh Pal","profile_url":"https://vbspu.academia.edu/SaurabhPal?f_ri=23995","photo":"https://0.academia-photos.com/340707/737364/1489470/s65_saurabh.pal.jpg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_25311406" data-work_id="25311406" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25311406/Recommendation_System_for_Engineering_Students_Specialization_Selection_Using_Predictive_Modeling">Recommendation System for Engineering Students' Specialization Selection Using Predictive Modeling</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Educational data mining (EDM) can be used in extracting useful patterns in students' academic records which may aid in management decision making on determination of engineering students' specialization track once the general engineering... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_25311406" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Educational data mining (EDM) can be used in extracting useful patterns in students' academic records which may aid in management decision making on determination of engineering students' specialization track once the general engineering academic requirements were completed. The objective of the research is to provide a specialization selection recommendation for engineering students through application of data mining algorithm and adoption of the rule sets generated by a predictive model. The attributes that may be significant in creating prediction were determined using correlation-based feature selection. Comparative analysis among known algorithms shows that the highest accuracy was considered. A decision tree classification model using WEKA and J48 produced an accuracy value of 80.06. The study revealed that Gender, Algebra, Calculus and physics courses found to have significant effect in predicting the engineering specialization, thus strengthening the general notion that for engineering students to be more successful, the academic performance with the above courses should be highly considered.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25311406" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="bd3a0d40476a8a695cfb5960579d78a8" rel="nofollow" data-download="{"attachment_id":45609564,"asset_id":25311406,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45609564/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2657630" href="https://sdiwc.academia.edu/TheSocietyofDigitalInformationandWirelessCommunications">SDIWC Organization</a><script data-card-contents-for-user="2657630" type="text/json">{"id":2657630,"first_name":"SDIWC","last_name":"Organization","domain_name":"sdiwc","page_name":"TheSocietyofDigitalInformationandWirelessCommunications","display_name":"SDIWC Organization","profile_url":"https://sdiwc.academia.edu/TheSocietyofDigitalInformationandWirelessCommunications?f_ri=23995","photo":"https://0.academia-photos.com/2657630/849179/1055710/s65_natalie.walker.jpg"}</script></span></span></li><li class="js-paper-rank-work_25311406 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="25311406"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 25311406, container: ".js-paper-rank-work_25311406", }); 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$(".js-view-count[data-work-id=25311406]").text(description); $(".js-view-count-work_25311406").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_25311406").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="25311406"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160433" href="https://www.academia.edu/Documents/in/Selection">Selection</a>, <script data-card-contents-for-ri="160433" type="text/json">{"id":160433,"name":"Selection","url":"https://www.academia.edu/Documents/in/Selection?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="298644" href="https://www.academia.edu/Documents/in/Recommendation_Systems">Recommendation Systems</a><script data-card-contents-for-ri="298644" type="text/json">{"id":298644,"name":"Recommendation Systems","url":"https://www.academia.edu/Documents/in/Recommendation_Systems?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=25311406]'), work: {"id":25311406,"title":"Recommendation System for Engineering Students' Specialization Selection Using Predictive Modeling","created_at":"2016-05-13T17:26:11.258-07:00","url":"https://www.academia.edu/25311406/Recommendation_System_for_Engineering_Students_Specialization_Selection_Using_Predictive_Modeling?f_ri=23995","dom_id":"work_25311406","summary":"Educational data mining (EDM) can be used in extracting useful patterns in students' academic records which may aid in management decision making on determination of engineering students' specialization track once the general engineering academic requirements were completed. The objective of the research is to provide a specialization selection recommendation for engineering students through application of data mining algorithm and adoption of the rule sets generated by a predictive model. The attributes that may be significant in creating prediction were determined using correlation-based feature selection. Comparative analysis among known algorithms shows that the highest accuracy was considered. A decision tree classification model using WEKA and J48 produced an accuracy value of 80.06. The study revealed that Gender, Algebra, Calculus and physics courses found to have significant effect in predicting the engineering specialization, thus strengthening the general notion that for engineering students to be more successful, the academic performance with the above courses should be highly considered.","downloadable_attachments":[{"id":45609564,"asset_id":25311406,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":2657630,"first_name":"SDIWC","last_name":"Organization","domain_name":"sdiwc","page_name":"TheSocietyofDigitalInformationandWirelessCommunications","display_name":"SDIWC Organization","profile_url":"https://sdiwc.academia.edu/TheSocietyofDigitalInformationandWirelessCommunications?f_ri=23995","photo":"https://0.academia-photos.com/2657630/849179/1055710/s65_natalie.walker.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":160433,"name":"Selection","url":"https://www.academia.edu/Documents/in/Selection?f_ri=23995","nofollow":false},{"id":298644,"name":"Recommendation Systems","url":"https://www.academia.edu/Documents/in/Recommendation_Systems?f_ri=23995","nofollow":false},{"id":327416,"name":"Predictive Modeling","url":"https://www.academia.edu/Documents/in/Predictive_Modeling?f_ri=23995"},{"id":2462785,"name":"Tree Classification","url":"https://www.academia.edu/Documents/in/Tree_Classification?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_14328575" data-work_id="14328575" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/14328575/EDUCATIONAL_DATA_MINING_APPLICATIONS">EDUCATIONAL DATA MINING APPLICATIONS</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The tools and techniques of data mining are being adopted by the industries to generate business intelligence for improving decision making. Education institutions are beginning to use data mining techniques for improving the services... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_14328575" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The tools and techniques of data mining are being adopted by the industries to generate business<br />intelligence for improving decision making. Education institutions are beginning to use data mining<br />techniques for improving the services they provide and for increasing student grades and retention. This<br />paper presents broad areas of applications in which educational data mining can be applied to e-learning.<br />The application areas discussed in this paper are:<br /> 1) User modelling<br />2) User grouping or profiling<br />3) Domain modelling and<br />4) Trend analysis.<br />A MathsTutor for school students of 6th, 7th and 8th grade is designed and implemented in 3 schools in<br />Tamilnadu. The student data are taken for analysis for the above said areas. This helps teachers, policy<br />makers, and administrators to understand how educational data mining work to support education related<br />decision making.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/14328575" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="61132a56daea1dca54313819ad64fccf" rel="nofollow" data-download="{"attachment_id":38269410,"asset_id":14328575,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/38269410/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33109891" href="https://independent.academia.edu/OJOURNAL">Operations Research and Applications: An International Journal (ORAJ)</a><script data-card-contents-for-user="33109891" type="text/json">{"id":33109891,"first_name":"Operations Research and Applications: An International Journal","last_name":"(ORAJ)","domain_name":"independent","page_name":"OJOURNAL","display_name":"Operations Research and Applications: An International Journal (ORAJ)","profile_url":"https://independent.academia.edu/OJOURNAL?f_ri=23995","photo":"https://0.academia-photos.com/33109891/9825633/100994342/s65_operations_research_and_applications_an_international_journal._oraj_.png"}</script></span></span></li><li class="js-paper-rank-work_14328575 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="14328575"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 14328575, container: ".js-paper-rank-work_14328575", }); 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$(".js-view-count[data-work-id=14328575]").text(description); $(".js-view-count-work_14328575").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_14328575").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="14328575"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="1609" href="https://www.academia.edu/Documents/in/E-learning">E-learning</a>, <script data-card-contents-for-ri="1609" type="text/json">{"id":1609,"name":"E-learning","url":"https://www.academia.edu/Documents/in/E-learning?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=14328575]'), work: {"id":14328575,"title":"EDUCATIONAL DATA MINING APPLICATIONS","created_at":"2015-07-23T05:02:44.760-07:00","url":"https://www.academia.edu/14328575/EDUCATIONAL_DATA_MINING_APPLICATIONS?f_ri=23995","dom_id":"work_14328575","summary":"The tools and techniques of data mining are being adopted by the industries to generate business\nintelligence for improving decision making. Education institutions are beginning to use data mining\ntechniques for improving the services they provide and for increasing student grades and retention. This\npaper presents broad areas of applications in which educational data mining can be applied to e-learning.\nThe application areas discussed in this paper are:\n 1) User modelling\n2) User grouping or profiling\n3) Domain modelling and\n4) Trend analysis.\nA MathsTutor for school students of 6th, 7th and 8th grade is designed and implemented in 3 schools in\nTamilnadu. The student data are taken for analysis for the above said areas. This helps teachers, policy\nmakers, and administrators to understand how educational data mining work to support education related\ndecision making. ","downloadable_attachments":[{"id":38269410,"asset_id":14328575,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33109891,"first_name":"Operations Research and Applications: An International Journal","last_name":"(ORAJ)","domain_name":"independent","page_name":"OJOURNAL","display_name":"Operations Research and Applications: An International Journal (ORAJ)","profile_url":"https://independent.academia.edu/OJOURNAL?f_ri=23995","photo":"https://0.academia-photos.com/33109891/9825633/100994342/s65_operations_research_and_applications_an_international_journal._oraj_.png"}],"research_interests":[{"id":1609,"name":"E-learning","url":"https://www.academia.edu/Documents/in/E-learning?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_7759291 coauthored" data-work_id="7759291" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/7759291/Capturing_Learner_Trajectories_in_Educational_Games_through_ADAGE_Assessment_Data_Aggregator_for_Game_Environments_A_Click_Stream_Data_Framework_for_Assessment_of_Learning_in_Play">Capturing Learner Trajectories in Educational Games through ADAGE (Assessment Data Aggregator for Game Environments): A Click-Stream Data Framework for Assessment of Learning in Play</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/7759291" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="43987ad0753a6ed80cb691c5165a132e" rel="nofollow" data-download="{"attachment_id":34274457,"asset_id":7759291,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/34274457/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="14252301" href="https://wisc.academia.edu/VElizabethOwen">V. Elizabeth Owen</a><script data-card-contents-for-user="14252301" type="text/json">{"id":14252301,"first_name":"V. Elizabeth","last_name":"Owen","domain_name":"wisc","page_name":"VElizabethOwen","display_name":"V. Elizabeth Owen","profile_url":"https://wisc.academia.edu/VElizabethOwen?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-7759291">+1</span><div class="hidden js-additional-users-7759291"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/SalmonAllison">Allison Salmon</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-7759291'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-7759291').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_7759291 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="7759291"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 7759291, container: ".js-paper-rank-work_7759291", }); 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$(".js-view-count[data-work-id=7759291]").text(description); $(".js-view-count-work_7759291").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_7759291").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="7759291"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="883" href="https://www.academia.edu/Documents/in/Game_studies">Game studies</a>, <script data-card-contents-for-ri="883" type="text/json">{"id":883,"name":"Game studies","url":"https://www.academia.edu/Documents/in/Game_studies?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1003" href="https://www.academia.edu/Documents/in/Educational_Technology">Educational Technology</a>, <script data-card-contents-for-ri="1003" type="text/json">{"id":1003,"name":"Educational Technology","url":"https://www.academia.edu/Documents/in/Educational_Technology?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1750" href="https://www.academia.edu/Documents/in/Assessment">Assessment</a>, <script data-card-contents-for-ri="1750" type="text/json">{"id":1750,"name":"Assessment","url":"https://www.academia.edu/Documents/in/Assessment?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2869" href="https://www.academia.edu/Documents/in/Digital_Media">Digital Media</a><script data-card-contents-for-ri="2869" type="text/json">{"id":2869,"name":"Digital Media","url":"https://www.academia.edu/Documents/in/Digital_Media?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=7759291]'), work: {"id":7759291,"title":"Capturing Learner Trajectories in Educational Games through ADAGE (Assessment Data Aggregator for Game Environments): A Click-Stream Data Framework for Assessment of Learning in Play","created_at":"2014-07-23T07:33:15.627-07:00","url":"https://www.academia.edu/7759291/Capturing_Learner_Trajectories_in_Educational_Games_through_ADAGE_Assessment_Data_Aggregator_for_Game_Environments_A_Click_Stream_Data_Framework_for_Assessment_of_Learning_in_Play?f_ri=23995","dom_id":"work_7759291","summary":null,"downloadable_attachments":[{"id":34274457,"asset_id":7759291,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":14252301,"first_name":"V. Elizabeth","last_name":"Owen","domain_name":"wisc","page_name":"VElizabethOwen","display_name":"V. 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It shows a strong influence and effect to the educational and health practitioners and the sectors. This paper offers some uses of virtual reality... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_37905976" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper discusses the significant roles of virtual reality in education and healthcare. It shows a strong influence and effect to the educational and health practitioners and the sectors. This paper offers some uses of virtual reality in education and healthcare. Also the paper attempt to bring about an authentic learning and assure healthy environment by incorporating immersive virtual reality technology.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/37905976" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d84ed83bac029cd1961a610978efc26d" rel="nofollow" data-download="{"attachment_id":57916230,"asset_id":37905976,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/57916230/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2002487" href="https://udusok-ng.academia.edu/NuradeenMukhtar">Nuradeen Mukhtar</a><script data-card-contents-for-user="2002487" type="text/json">{"id":2002487,"first_name":"Nuradeen","last_name":"Mukhtar","domain_name":"udusok-ng","page_name":"NuradeenMukhtar","display_name":"Nuradeen Mukhtar","profile_url":"https://udusok-ng.academia.edu/NuradeenMukhtar?f_ri=23995","photo":"https://0.academia-photos.com/2002487/959270/13003125/s65_nuradeen.mukhtar.jpg"}</script></span></span></li><li class="js-paper-rank-work_37905976 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="37905976"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 37905976, container: ".js-paper-rank-work_37905976", }); 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data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ce61e6be1331fac04288650528453259" rel="nofollow" data-download="{"attachment_id":37059928,"asset_id":11569658,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/37059928/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="28245131" href="https://gcwus.academia.edu/HaniaMalik">Hania Malik</a><script data-card-contents-for-user="28245131" type="text/json">{"id":28245131,"first_name":"Hania","last_name":"Malik","domain_name":"gcwus","page_name":"HaniaMalik","display_name":"Hania Malik","profile_url":"https://gcwus.academia.edu/HaniaMalik?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_11569658 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="11569658"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 11569658, container: ".js-paper-rank-work_11569658", }); });</script></li><li class="js-percentile-work_11569658 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 11569658; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_11569658"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_11569658 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="11569658"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 11569658; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=11569658]").text(description); $(".js-view-count-work_11569658").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_11569658").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="11569658"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="1695" href="https://www.academia.edu/Documents/in/Distance_Education">Distance Education</a>, <script data-card-contents-for-ri="1695" type="text/json">{"id":1695,"name":"Distance Education","url":"https://www.academia.edu/Documents/in/Distance_Education?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="69604" href="https://www.academia.edu/Documents/in/Academic_Analytics">Academic Analytics</a><script data-card-contents-for-ri="69604" type="text/json">{"id":69604,"name":"Academic Analytics","url":"https://www.academia.edu/Documents/in/Academic_Analytics?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=11569658]'), work: {"id":11569658,"title":"A survey of educational data A survey of educational data-mining research mining research","created_at":"2015-03-21T09:12:55.472-07:00","url":"https://www.academia.edu/11569658/A_survey_of_educational_data_A_survey_of_educational_data_mining_research_mining_research?f_ri=23995","dom_id":"work_11569658","summary":null,"downloadable_attachments":[{"id":37059928,"asset_id":11569658,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":28245131,"first_name":"Hania","last_name":"Malik","domain_name":"gcwus","page_name":"HaniaMalik","display_name":"Hania Malik","profile_url":"https://gcwus.academia.edu/HaniaMalik?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":1695,"name":"Distance Education","url":"https://www.academia.edu/Documents/in/Distance_Education?f_ri=23995","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false},{"id":69604,"name":"Academic Analytics","url":"https://www.academia.edu/Documents/in/Academic_Analytics?f_ri=23995","nofollow":false},{"id":78457,"name":"Learning Analytics","url":"https://www.academia.edu/Documents/in/Learning_Analytics?f_ri=23995"},{"id":677774,"name":"Institutional","url":"https://www.academia.edu/Documents/in/Institutional?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_37781501" data-work_id="37781501" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/37781501/Predicting_Students_Performance_Using_Classification_Techniques_in_Data_Mining">Predicting Students' Performance Using Classification Techniques in Data Mining</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Role of education is very critical for the development of any country. So it is the responsibility of each and every person to do something for the betterment of education. Taking this fact into consideration we start working on the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_37781501" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Role of education is very critical for the development of any country. So it is the responsibility of each and every person to do something for the betterment of education. Taking this fact into consideration we start working on the education system. Education system ranging from basic to higher education. Now a day education system generates a lots of data related to student. If we cannot analyze that data properly then that data is useless. With the help of data mining techniques we can find the hidden information from the data collected for the different educational setting. With the help of that information we can review our educational process or make improvement in our education system. Here in this article we are considering a case of an engineering college student and try to predict the final result in advance. The result of the prediction provides timely help to those students who are on risk of failure in the final examination. There are different techniques of data mining are available and we are using J48, RandomForest, and ADTree to predict the performance of the student in their final examination. On the basis of this predication we can make a decision whether the student will be promoted to next year or not. We the help of the result we can improve the performance of the student who are on risk of fail or promoted. After the declaration of the final result of the student, result is fed into the system and hence the result will analysed for the next semester. The comparative result shows that, prediction help in the improvement of overall result of the weaker students.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/37781501" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ce2501a3f946b78594cc2c3e37a10cb3" rel="nofollow" data-download="{"attachment_id":57778190,"asset_id":37781501,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/57778190/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8037161" href="https://lovely-professional-university.academia.edu/MukeshKumar2">Dr Mukesh Kumar</a><script data-card-contents-for-user="8037161" type="text/json">{"id":8037161,"first_name":"Dr Mukesh","last_name":"Kumar","domain_name":"lovely-professional-university","page_name":"MukeshKumar2","display_name":"Dr Mukesh Kumar","profile_url":"https://lovely-professional-university.academia.edu/MukeshKumar2?f_ri=23995","photo":"https://0.academia-photos.com/8037161/3220392/93073688/s65_dr_mukesh.kumar.jpeg"}</script></span></span></li><li class="js-paper-rank-work_37781501 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="37781501"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 37781501, container: ".js-paper-rank-work_37781501", }); });</script></li><li class="js-percentile-work_37781501 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 37781501; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_37781501"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_37781501 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="37781501"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 37781501; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=37781501]").text(description); $(".js-view-count-work_37781501").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_37781501").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="37781501"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a><script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=37781501]'), work: {"id":37781501,"title":"Predicting Students' Performance Using Classification Techniques in Data Mining","created_at":"2018-11-15T10:15:23.043-08:00","url":"https://www.academia.edu/37781501/Predicting_Students_Performance_Using_Classification_Techniques_in_Data_Mining?f_ri=23995","dom_id":"work_37781501","summary":"Role of education is very critical for the development of any country. So it is the responsibility of each and every person to do something for the betterment of education. Taking this fact into consideration we start working on the education system. Education system ranging from basic to higher education. Now a day education system generates a lots of data related to student. If we cannot analyze that data properly then that data is useless. With the help of data mining techniques we can find the hidden information from the data collected for the different educational setting. With the help of that information we can review our educational process or make improvement in our education system. Here in this article we are considering a case of an engineering college student and try to predict the final result in advance. The result of the prediction provides timely help to those students who are on risk of failure in the final examination. There are different techniques of data mining are available and we are using J48, RandomForest, and ADTree to predict the performance of the student in their final examination. On the basis of this predication we can make a decision whether the student will be promoted to next year or not. We the help of the result we can improve the performance of the student who are on risk of fail or promoted. After the declaration of the final result of the student, result is fed into the system and hence the result will analysed for the next semester. The comparative result shows that, prediction help in the improvement of overall result of the weaker students.","downloadable_attachments":[{"id":57778190,"asset_id":37781501,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":8037161,"first_name":"Dr Mukesh","last_name":"Kumar","domain_name":"lovely-professional-university","page_name":"MukeshKumar2","display_name":"Dr Mukesh Kumar","profile_url":"https://lovely-professional-university.academia.edu/MukeshKumar2?f_ri=23995","photo":"https://0.academia-photos.com/8037161/3220392/93073688/s65_dr_mukesh.kumar.jpeg"}],"research_interests":[{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18134097 coauthored" data-work_id="18134097" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18134097/Learning_analytics_should_not_promote_one_size_fits_all_The_effects_of_course_specific_technology_use_in_predicting_academic_success">Learning analytics should not promote one size fits all: The effects of course-specific technology use in predicting academic success</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This study examined the extent to which instructional conditions influence the prediction of academic success in nine undergraduate courses offered in a blended learning model (n = 4134). The study illustrates the differences in... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_18134097" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This study examined the extent to which instructional conditions influence the prediction of academic success in nine undergraduate courses offered in a blended learning model (n = 4134). The study illustrates the differences in predictive power and significant predictors between course-specific models and generalized predictive models. The results suggest that it is imperative for learning analytics research to account for the diverse ways technology is adopted and applied in course-specific contexts. The differences in technology use, especially those related to whether and how learners use the learning management system, require consideration before the log-data can be merged to create a generalized model for predicting academic success. A lack of attention to instructional conditions can lead to an over or under estimation of the effects of LMS features on students' academic success. These findings have broader implications for institutions seeking generalized and portable models for identifying students at risk of academic failure.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18134097" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1f7446dccee5c7b1a36248afe11b8764" rel="nofollow" data-download="{"attachment_id":39893104,"asset_id":18134097,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39893104/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="170672" href="https://edinburgh.academia.edu/DraganGasevic">Dragan Gasevic</a><script data-card-contents-for-user="170672" type="text/json">{"id":170672,"first_name":"Dragan","last_name":"Gasevic","domain_name":"edinburgh","page_name":"DraganGasevic","display_name":"Dragan Gasevic","profile_url":"https://edinburgh.academia.edu/DraganGasevic?f_ri=23995","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-18134097">+2</span><div class="hidden js-additional-users-18134097"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://edinburgh.academia.edu/DanijelaGasevic">Danijela Gasevic</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/TimRogers16">Tim Rogers</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-18134097'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-18134097').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_18134097 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="18134097"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 18134097; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=18134097]").text(description); $(".js-view-count-work_18134097").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18134097").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18134097"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="922" href="https://www.academia.edu/Documents/in/Education">Education</a>, <script data-card-contents-for-ri="922" type="text/json">{"id":922,"name":"Education","url":"https://www.academia.edu/Documents/in/Education?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1000" href="https://www.academia.edu/Documents/in/Instructional_Design">Instructional Design</a>, <script data-card-contents-for-ri="1000" type="text/json">{"id":1000,"name":"Instructional Design","url":"https://www.academia.edu/Documents/in/Instructional_Design?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1003" href="https://www.academia.edu/Documents/in/Educational_Technology">Educational Technology</a>, <script data-card-contents-for-ri="1003" type="text/json">{"id":1003,"name":"Educational Technology","url":"https://www.academia.edu/Documents/in/Educational_Technology?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1609" href="https://www.academia.edu/Documents/in/E-learning">E-learning</a><script data-card-contents-for-ri="1609" type="text/json">{"id":1609,"name":"E-learning","url":"https://www.academia.edu/Documents/in/E-learning?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18134097]'), work: {"id":18134097,"title":"Learning analytics should not promote one size fits all: The effects of course-specific technology use in predicting academic success","created_at":"2015-11-11T00:59:25.902-08:00","url":"https://www.academia.edu/18134097/Learning_analytics_should_not_promote_one_size_fits_all_The_effects_of_course_specific_technology_use_in_predicting_academic_success?f_ri=23995","dom_id":"work_18134097","summary":"This study examined the extent to which instructional conditions influence the prediction of academic success in nine undergraduate courses offered in a blended learning model (n = 4134). The study illustrates the differences in predictive power and significant predictors between course-specific models and generalized predictive models. The results suggest that it is imperative for learning analytics research to account for the diverse ways technology is adopted and applied in course-specific contexts. The differences in technology use, especially those related to whether and how learners use the learning management system, require consideration before the log-data can be merged to create a generalized model for predicting academic success. A lack of attention to instructional conditions can lead to an over or under estimation of the effects of LMS features on students' academic success. These findings have broader implications for institutions seeking generalized and portable models for identifying students at risk of academic failure.","downloadable_attachments":[{"id":39893104,"asset_id":18134097,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":170672,"first_name":"Dragan","last_name":"Gasevic","domain_name":"edinburgh","page_name":"DraganGasevic","display_name":"Dragan Gasevic","profile_url":"https://edinburgh.academia.edu/DraganGasevic?f_ri=23995","photo":"/images/s65_no_pic.png"},{"id":29268690,"first_name":"Danijela","last_name":"Gasevic","domain_name":"edinburgh","page_name":"DanijelaGasevic","display_name":"Danijela Gasevic","profile_url":"https://edinburgh.academia.edu/DanijelaGasevic?f_ri=23995","photo":"/images/s65_no_pic.png"},{"id":38218566,"first_name":"Tim","last_name":"Rogers","domain_name":"independent","page_name":"TimRogers16","display_name":"Tim Rogers","profile_url":"https://independent.academia.edu/TimRogers16?f_ri=23995","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":922,"name":"Education","url":"https://www.academia.edu/Documents/in/Education?f_ri=23995","nofollow":false},{"id":1000,"name":"Instructional Design","url":"https://www.academia.edu/Documents/in/Instructional_Design?f_ri=23995","nofollow":false},{"id":1003,"name":"Educational Technology","url":"https://www.academia.edu/Documents/in/Educational_Technology?f_ri=23995","nofollow":false},{"id":1609,"name":"E-learning","url":"https://www.academia.edu/Documents/in/E-learning?f_ri=23995","nofollow":false},{"id":6292,"name":"Self-regulated Learning","url":"https://www.academia.edu/Documents/in/Self-regulated_Learning?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":78457,"name":"Learning Analytics","url":"https://www.academia.edu/Documents/in/Learning_Analytics?f_ri=23995"},{"id":81405,"name":"Student retention","url":"https://www.academia.edu/Documents/in/Student_retention?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17705939" data-work_id="17705939" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17705939/Application_of_Data_Mining_Technique_for_Prediction_of_Academic_Performance_of_Student_A_Literature_survey">Application of Data Mining Technique for Prediction of Academic Performance of Student A Literature survey</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Application of data mining in the educational Systems can be directed to support the specific need of each of the participants in the education system and the process. Students are required to add the recommendation for additional... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_17705939" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Application of data mining in the educational Systems can be directed to support the specific need of each of the participants in the education system and the process. Students are required to add the recommendation for additional activities, teaching material and task that would favor and improve his/her learning process. Professors would have the feedback, possibilities to classify students into group’s base on their need for guidance and monitoring, to find the mistakes, and find the effective actions. There are so many prediction model are available with difference approach and techniques in student performance prediction was reported by researchers, but there is no possibility if there are any predictors that accurately determine whether a student will be an genius, a drop out, or an average performer. The target of this study was to apply the k-map method for mining data to analyze the relationships in between student’s success and their behavior and to develop model for Prediction of Academic Performance of Students. This would be done by using Support Vector Machine (SVM) classifications and kernel k-map clustering mechanism. By Predicting student’s performance can help to identify the students who are at risk of failure and thus management can provide timely help and take essential steps to coach the students to improve performance.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17705939" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d50aee6199ea23a0de98b0250ec0e13c" rel="nofollow" data-download="{"attachment_id":39665837,"asset_id":17705939,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39665837/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4270915" href="https://ijritcc.academia.edu/ijritcc">International Journal IJRITCC</a><script data-card-contents-for-user="4270915" type="text/json">{"id":4270915,"first_name":"International Journal","last_name":"IJRITCC","domain_name":"ijritcc","page_name":"ijritcc","display_name":"International Journal IJRITCC","profile_url":"https://ijritcc.academia.edu/ijritcc?f_ri=23995","photo":"https://0.academia-photos.com/4270915/1697386/11514623/s65_international_journal.ijritcc.jpeg"}</script></span></span></li><li class="js-paper-rank-work_17705939 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="17705939"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 17705939, container: ".js-paper-rank-work_17705939", }); 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$(".js-view-count[data-work-id=17705939]").text(description); $(".js-view-count-work_17705939").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_17705939").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="17705939"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">23</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="48" href="https://www.academia.edu/Documents/in/Engineering">Engineering</a>, <script data-card-contents-for-ri="48" type="text/json">{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="50" href="https://www.academia.edu/Documents/in/Electronic_Engineering">Electronic Engineering</a>, <script data-card-contents-for-ri="50" type="text/json">{"id":50,"name":"Electronic Engineering","url":"https://www.academia.edu/Documents/in/Electronic_Engineering?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="78" href="https://www.academia.edu/Documents/in/Control_Systems_Engineering">Control Systems Engineering</a>, <script data-card-contents-for-ri="78" type="text/json">{"id":78,"name":"Control Systems Engineering","url":"https://www.academia.edu/Documents/in/Control_Systems_Engineering?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a><script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17705939]'), work: {"id":17705939,"title":"Application of Data Mining Technique for Prediction of Academic Performance of Student A Literature survey","created_at":"2015-11-03T23:45:38.354-08:00","url":"https://www.academia.edu/17705939/Application_of_Data_Mining_Technique_for_Prediction_of_Academic_Performance_of_Student_A_Literature_survey?f_ri=23995","dom_id":"work_17705939","summary":"Application of data mining in the educational Systems can be directed to support the specific need of each of the participants in the education system and the process. Students are required to add the recommendation for additional activities, teaching material and task that would favor and improve his/her learning process. Professors would have the feedback, possibilities to classify students into group’s base on their need for guidance and monitoring, to find the mistakes, and find the effective actions. There are so many prediction model are available with difference approach and techniques in student performance prediction was reported by researchers, but there is no possibility if there are any predictors that accurately determine whether a student will be an genius, a drop out, or an average performer. The target of this study was to apply the k-map method for mining data to analyze the relationships in between student’s success and their behavior and to develop model for Prediction of Academic Performance of Students. This would be done by using Support Vector Machine (SVM) classifications and kernel k-map clustering mechanism. By Predicting student’s performance can help to identify the students who are at risk of failure and thus management can provide timely help and take essential steps to coach the students to improve performance.","downloadable_attachments":[{"id":39665837,"asset_id":17705939,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4270915,"first_name":"International Journal","last_name":"IJRITCC","domain_name":"ijritcc","page_name":"ijritcc","display_name":"International Journal IJRITCC","profile_url":"https://ijritcc.academia.edu/ijritcc?f_ri=23995","photo":"https://0.academia-photos.com/4270915/1697386/11514623/s65_international_journal.ijritcc.jpeg"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=23995","nofollow":false},{"id":50,"name":"Electronic Engineering","url":"https://www.academia.edu/Documents/in/Electronic_Engineering?f_ri=23995","nofollow":false},{"id":78,"name":"Control Systems Engineering","url":"https://www.academia.edu/Documents/in/Control_Systems_Engineering?f_ri=23995","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false},{"id":449,"name":"Software Engineering","url":"https://www.academia.edu/Documents/in/Software_Engineering?f_ri=23995"},{"id":491,"name":"Information Technology","url":"https://www.academia.edu/Documents/in/Information_Technology?f_ri=23995"},{"id":922,"name":"Education","url":"https://www.academia.edu/Documents/in/Education?f_ri=23995"},{"id":923,"name":"Technology","url":"https://www.academia.edu/Documents/in/Technology?f_ri=23995"},{"id":1003,"name":"Educational Technology","url":"https://www.academia.edu/Documents/in/Educational_Technology?f_ri=23995"},{"id":1380,"name":"Computer Engineering","url":"https://www.academia.edu/Documents/in/Computer_Engineering?f_ri=23995"},{"id":1601,"name":"Teacher Education","url":"https://www.academia.edu/Documents/in/Teacher_Education?f_ri=23995"},{"id":1736,"name":"Science Education","url":"https://www.academia.edu/Documents/in/Science_Education?f_ri=23995"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995"},{"id":2065,"name":"Research Methodology","url":"https://www.academia.edu/Documents/in/Research_Methodology?f_ri=23995"},{"id":3429,"name":"Educational Research","url":"https://www.academia.edu/Documents/in/Educational_Research?f_ri=23995"},{"id":4252,"name":"Computer Networks","url":"https://www.academia.edu/Documents/in/Computer_Networks?f_ri=23995"},{"id":4758,"name":"Electronics","url":"https://www.academia.edu/Documents/in/Electronics?f_ri=23995"},{"id":14305,"name":"Industrial Engineering","url":"https://www.academia.edu/Documents/in/Industrial_Engineering?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":26860,"name":"Cloud Computing","url":"https://www.academia.edu/Documents/in/Cloud_Computing?f_ri=23995"},{"id":76424,"name":"Academic Performance","url":"https://www.academia.edu/Documents/in/Academic_Performance?f_ri=23995"},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995"},{"id":1121494,"name":"Student","url":"https://www.academia.edu/Documents/in/Student?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_26252824" data-work_id="26252824" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/26252824/A_Decision_Making_Model_for_Human_Resource_Management_in_Organizations_using_Data_Mining_and_Predictive_Analytics">A Decision Making Model for Human Resource Management in Organizations using Data Mining and Predictive Analytics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Abstract — The development of a decision-making model for Human Resource Management (HRM) in organizations especially for multinational companies can be encouraged considering the fact that HRM plays a lead role in determining the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_26252824" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Abstract — The development of a decision-making model for Human Resource Management (HRM) in organizations especially for multinational companies can be encouraged considering the fact that HRM plays a lead role in determining the effectiveness of organizations’ endurance. The HRM generally maintains evaluation practices and systems impelling employee behavior, commitment, and performance. It is the responsibility of the HRM to dig best talents around the world, look after training, evaluate employee performance, give away rewards and ultimately keep a right environment in the company. As every strategy of an organization is totally or somewhat related to the talents present, it becomes essential to provide a framework that accurately predicts talent and workforce. When human resource data is accessed for decision making, different methods can be used to extract the best knowledge out of available data. Data mining is widely considered for extracting insights from data to make decisions whereas predictive analytics is known for state-of-the-art accuracy in decisions. The proposed model can be helpful in improving effectiveness and efficiency of HR system that will optimize business outcome. This paper is an attempt to provide a decision-making framework for Human Resource related decisions comprising data mining and predictive analytics.<br /><br />Index Terms— Data Mining, Decision Making, Human Resource Management, Predictive Analytics, Talent Management.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/26252824" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="cca3201a142089c77869757184a35981" rel="nofollow" data-download="{"attachment_id":46568117,"asset_id":26252824,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46568117/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2328357" href="https://independent.academia.edu/JournalofComputerScienceIJCSIS">Journal of Computer Science IJCSIS</a><script data-card-contents-for-user="2328357" type="text/json">{"id":2328357,"first_name":"Journal of Computer Science","last_name":"IJCSIS","domain_name":"independent","page_name":"JournalofComputerScienceIJCSIS","display_name":"Journal of Computer Science IJCSIS","profile_url":"https://independent.academia.edu/JournalofComputerScienceIJCSIS?f_ri=23995","photo":"https://0.academia-photos.com/2328357/8085511/9052483/s65_journal_of_computer_science.ijcsis.jpg"}</script></span></span></li><li class="js-paper-rank-work_26252824 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="26252824"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 26252824, container: ".js-paper-rank-work_26252824", }); 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The HRM generally maintains evaluation practices and systems impelling employee behavior, commitment, and performance. It is the responsibility of the HRM to dig best talents around the world, look after training, evaluate employee performance, give away rewards and ultimately keep a right environment in the company. As every strategy of an organization is totally or somewhat related to the talents present, it becomes essential to provide a framework that accurately predicts talent and workforce. When human resource data is accessed for decision making, different methods can be used to extract the best knowledge out of available data. Data mining is widely considered for extracting insights from data to make decisions whereas predictive analytics is known for state-of-the-art accuracy in decisions. The proposed model can be helpful in improving effectiveness and efficiency of HR system that will optimize business outcome. This paper is an attempt to provide a decision-making framework for Human Resource related decisions comprising data mining and predictive analytics.\n\nIndex Terms— Data Mining, Decision Making, Human Resource Management, Predictive Analytics, Talent Management.\n","downloadable_attachments":[{"id":46568117,"asset_id":26252824,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":2328357,"first_name":"Journal of Computer Science","last_name":"IJCSIS","domain_name":"independent","page_name":"JournalofComputerScienceIJCSIS","display_name":"Journal of Computer Science IJCSIS","profile_url":"https://independent.academia.edu/JournalofComputerScienceIJCSIS?f_ri=23995","photo":"https://0.academia-photos.com/2328357/8085511/9052483/s65_journal_of_computer_science.ijcsis.jpg"}],"research_interests":[{"id":37,"name":"Information Systems","url":"https://www.academia.edu/Documents/in/Information_Systems?f_ri=23995","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=23995","nofollow":false},{"id":491,"name":"Information Technology","url":"https://www.academia.edu/Documents/in/Information_Technology?f_ri=23995","nofollow":false},{"id":1380,"name":"Computer Engineering","url":"https://www.academia.edu/Documents/in/Computer_Engineering?f_ri=23995","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995"},{"id":7454,"name":"Information Communication Technology","url":"https://www.academia.edu/Documents/in/Information_Communication_Technology?f_ri=23995"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=23995"},{"id":39693,"name":"Distributed Data Mining","url":"https://www.academia.edu/Documents/in/Distributed_Data_Mining?f_ri=23995"},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=23995"},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=23995"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_36086763" data-work_id="36086763" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/36086763/An_Algorithm_for_Predictive_Data_Mining_Approach_in_Medical_Diagnosis">An Algorithm for Predictive Data Mining Approach in Medical Diagnosis</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The Healthcare industry contains big and complex data that may be required in order to discover fascinating pattern of diseases & makes effective decisions with the help of different machine learning techniques. Advanced data mining... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_36086763" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The Healthcare industry contains big and complex data that may be required in order to discover fascinating pattern of diseases & makes effective decisions with the help of different machine learning<br />techniques. Advanced data mining techniques are used to discover knowledge in database and for medical research. This paper has analyzed prediction systems for Diabetes, Kidney and Liver disease using more number of input attributes. The data mining classification techniques, namely Support Vector Machine(SVM) and Random Forest (RF) are analyzed on Diabetes, Kidney and Liver disease database.<br />The performance of these techniques is compared, based on precision, recall, accuracy, f_measure as well as time. As a result of study the proposed algorithm is designed using SVM and RF algorithm and the<br />experimental result shows the accuracy of 99.35%, 99.37 and 99.14 on diabetes, kidney and liver disease respectively.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/36086763" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="cb959333f1180d84168a90fc3c3d6c86" rel="nofollow" data-download="{"attachment_id":55975904,"asset_id":36086763,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/55975904/download_file?st=MTczMjM5MDYwMiw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="21255813" href="https://independent.academia.edu/IjcsitJournal">International Journal of Computer Science and Information Technology ( IJCSIT ) INSPEC ,WJCI Indexed</a><script data-card-contents-for-user="21255813" type="text/json">{"id":21255813,"first_name":"International Journal of Computer Science and Information Technology","last_name":"( IJCSIT ) INSPEC ,WJCI Indexed","domain_name":"independent","page_name":"IjcsitJournal","display_name":"International Journal of Computer Science and Information Technology ( IJCSIT ) INSPEC ,WJCI Indexed","profile_url":"https://independent.academia.edu/IjcsitJournal?f_ri=23995","photo":"https://0.academia-photos.com/21255813/5872009/139167812/s65_international_journal_of_computer_science_and_information_technology._ijcsit_inspec_wjci_indexed.jpg"}</script></span></span></li><li class="js-paper-rank-work_36086763 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="36086763"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 36086763, container: ".js-paper-rank-work_36086763", }); 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$(".js-view-count[data-work-id=36086763]").text(description); $(".js-view-count-work_36086763").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_36086763").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="36086763"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">30</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4095" href="https://www.academia.edu/Documents/in/Classification_Machine_Learning_">Classification (Machine Learning)</a>, <script data-card-contents-for-ri="4095" type="text/json">{"id":4095,"name":"Classification (Machine Learning)","url":"https://www.academia.edu/Documents/in/Classification_Machine_Learning_?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="5486" href="https://www.academia.edu/Documents/in/Clustering_and_Classification_Methods">Clustering and Classification Methods</a>, <script data-card-contents-for-ri="5486" type="text/json">{"id":5486,"name":"Clustering and Classification Methods","url":"https://www.academia.edu/Documents/in/Clustering_and_Classification_Methods?f_ri=23995","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9447" href="https://www.academia.edu/Documents/in/Stream_Mining_Data_Mining_">Stream Mining (Data Mining)</a><script data-card-contents-for-ri="9447" type="text/json">{"id":9447,"name":"Stream Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Stream_Mining_Data_Mining_?f_ri=23995","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=36086763]'), work: {"id":36086763,"title":"An Algorithm for Predictive Data Mining Approach in Medical Diagnosis","created_at":"2018-03-05T22:45:54.885-08:00","url":"https://www.academia.edu/36086763/An_Algorithm_for_Predictive_Data_Mining_Approach_in_Medical_Diagnosis?f_ri=23995","dom_id":"work_36086763","summary":"The Healthcare industry contains big and complex data that may be required in order to discover fascinating pattern of diseases \u0026 makes effective decisions with the help of different machine learning\ntechniques. Advanced data mining techniques are used to discover knowledge in database and for medical research. This paper has analyzed prediction systems for Diabetes, Kidney and Liver disease using more number of input attributes. The data mining classification techniques, namely Support Vector Machine(SVM) and Random Forest (RF) are analyzed on Diabetes, Kidney and Liver disease database.\nThe performance of these techniques is compared, based on precision, recall, accuracy, f_measure as well as time. As a result of study the proposed algorithm is designed using SVM and RF algorithm and the\nexperimental result shows the accuracy of 99.35%, 99.37 and 99.14 on diabetes, kidney and liver disease respectively. 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