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An Educational Data Mining System for Advising Higher Education Students
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/></div></noscript> <!-- /Yandex.Metrika counter --> <!-- Matomo --> <!-- End Matomo Code --> <title>An Educational Data Mining System for Advising Higher Education Students</title> <meta name="description" content="An Educational Data Mining System for Advising Higher Education Students"> <meta name="keywords" content="Classification, Clustering, Educational Data Mining (EDM), Machine Learning."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="An Educational Data Mining System for Advising Higher Education Students"> <meta name="citation_author" content="Heba Mohammed Nagy"> <meta name="citation_author" content="Walid Mohamed Aly"> <meta name="citation_author" content="Osama Fathy Hegazy"> <meta name="citation_publication_date" content="2013/09/02"> <meta name="citation_journal_title" content="International Journal of Computer and Information 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class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Heba%20Mohammed%20Nagy">Heba Mohammed Nagy</a>, <a href="https://publications.waset.org/search?q=Walid%20Mohamed%20Aly"> Walid Mohamed Aly</a>, <a href="https://publications.waset.org/search?q=Osama%20Fathy%20Hegazy"> Osama Fathy Hegazy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Educational data mining is a specific data mining field applied to data originating from educational environments, it relies on different approaches to discover hidden knowledge from the available data. Among these approaches are machine learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.</p> <p>In our research, we propose a “Student Advisory Framework” that utilizes classification and clustering to build an intelligent system. This system can be used to provide pieces of consultations to a first year university student to pursue a certain education track where he/she will likely succeed in, aiming to decrease the high rate of academic failure among these students. A real case study in Cairo Higher Institute for Engineering, Computer Science and Management is presented using real dataset collected from 2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.</p> <iframe src="https://publications.waset.org/16952.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Classification" title="Classification">Classification</a>, <a href="https://publications.waset.org/search?q=Clustering" title=" Clustering"> Clustering</a>, <a href="https://publications.waset.org/search?q=Educational%20Data%20Mining%20%28EDM%29" title=" Educational Data Mining (EDM)"> Educational Data Mining (EDM)</a>, <a href="https://publications.waset.org/search?q=Machine%20Learning." title=" Machine Learning."> Machine Learning.</a> </p> <p class="card-text"><strong>Digital Object Identifier (DOI):</strong> <a href="https://doi.org/10.5281/zenodo.1088158" target="_blank">doi.org/10.5281/zenodo.1088158</a> </p> <a href="https://publications.waset.org/16952/an-educational-data-mining-system-for-advising-higher-education-students" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/16952/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/16952/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/16952/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/16952/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/16952/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/16952/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/16952/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/16952/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/16952/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/16952/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/16952.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">5213</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] T. M. Mitchell. Machine Learning. McGraw-Hill, New York, 1997. <br>[2] Shi Na, Liu Xumin, and Guan Yong. Research on k-means clustering algorithm: An improved k-means clustering algorithm. In Intelligent Information Technology and Security Informatics (IITSI), 2010 Third International Symposium on, pages 63–67, 2010. <br>[3] A. M. El-Halees M. M. Abu Tair. Mining educational data to improve students’ performance: A case study. International Journal of Information and Communication Technology Research, 2(2): 140–146, April 2011. <br>[4] S. Karthik M. Sukanya, S. Biruntha and T. Kalaikumaran. Data mining: Performance improvement in education sector using classification and clustering algorithm. In Proceedings of the International Conference on Computing and Control Engineering, ICCCE 2012, 2012. <br>[5] Mahfuza Haque Md. Hedayetul Islam Shovon. Prediction of student academic performance by an application of k-means clustering algorithm. International Journal of Advanced Research in Computer Science and Software Engineering, 2(7): 353–355, July 2012. <br>[6] M. tech Er. Rimmy Chuchra. Use of data mining techniques for the evaluation of student performance: a case study. International Journal of Computer Science and Management Research, 1(3): 425–433, October 2012. <br>[7] Brijesh Kumar Bhardwaj and Saurabh Pal. Data mining: A prediction for performance improvement using classification. (IJCSIS) International Journal of Computer Science and Information Security, 9(4), April 2011. <br>[8] Md. Hedayetul Islam Shovon and Mahfuza Haque. An approach of improving students academic performance by using k-means clustering algorithm and decision tree. 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