Cluster Analysis of Behavior of E-learners
Mandeep Kaur1, Kewal krishan2
1Mandeep Kaur M.tech in Information Technology, Lovely professional University, Phagwara, India.
2Kewal krishan, Department of CSE/IT , Lovely professional University, Phagwara, India.
Manuscript received on April 04, 2013. | Revised Manuscript received on April 28, 2013. | Manuscript published on May 05, 2013. | PP: 344-346 | Volume-3, Issue-2, May 2013. | Retrieval Number: B1549053213/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: E-learning is a modern way of learning in which teachers and students don’t have actual contact. It’s a web based or online learning in which e-learners enroll in educational courses and can learn online. Unlike traditional classrooms in which some students don’t put their queries to teachers due to hesitation e-learners can put any kind of queries to teachers because they don’t have face to face contact. In Elearning system students have different kind of behavior. Though e-learning courses are designed on the basis of “same content fits all” yet students feel difficulty because every students’ learning ability depends upon their individual learning ability. This study proposes the analysis of students’ behavior using data mining tools and techniques. Classification and clustering techniques are used to analyze the relationship between usage of courses and performance of students. Students’performance depends upon their grades, how much time they spend in learning, usage of courses as well as richness of course quality. The study uses data from previous approach, E-learning data from Greek University. This paper uses same approach with different data mining tools and techniques.
Keywords: E-learning, data mining, classification, clustering.