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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&nbsp; data mining&nbsp; is&nbsp; a&nbsp; specific&nbsp; data&nbsp;&nbsp; mining field applied to data originating from educational environments, it relies on different&nbsp; approaches to discover hidden knowledge&nbsp; from&nbsp; the&nbsp; available&nbsp;&nbsp; data. Among these approaches are&nbsp;&nbsp; machine&nbsp;&nbsp; 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&nbsp; our&nbsp; research, we propose&nbsp; a &ldquo;Student&nbsp; Advisory&nbsp; Framework&rdquo; that&nbsp; utilizes&nbsp; classification&nbsp; and&nbsp; clustering&nbsp; to&nbsp; build&nbsp; an&nbsp; intelligent system. This system can be used to provide pieces of consultations to a first year&nbsp; university&nbsp; student to&nbsp; pursue a&nbsp; certain&nbsp;&nbsp; education&nbsp;&nbsp; track&nbsp;&nbsp; where&nbsp; he/she&nbsp; will&nbsp; likely&nbsp; succeed&nbsp; in, aiming&nbsp; to&nbsp; decrease&nbsp;&nbsp; the&nbsp; high&nbsp; rate&nbsp;&nbsp; of&nbsp; academic&nbsp; failure&nbsp;&nbsp; among these&nbsp; students.&nbsp; A real case study&nbsp; in Cairo&nbsp; Higher&nbsp; Institute&nbsp; for Engineering, Computer&nbsp; Science&nbsp; and&nbsp; Management&nbsp; is&nbsp; presented using&nbsp; real&nbsp; dataset&nbsp;&nbsp; collected&nbsp; from&nbsp; 2000&minus;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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