Personalization of e-Learning Using Data Mining
The development of the World Wide Web has opened new avenues in the arena of educational research. E-learning is a process in which education is imparted through digital means. E-learning mainly focuses on learner-centric training rather than teacher-centric training, which has been in practice in traditional teaching. One of the crucial aspects of learner-centric training is the personalization of the learning process. The learner is directed to learn from the web-based contents. Online examinations are conducted to assess the learner. The scores obtained by the learner are analyzed with the contents traversed by the learner which forms the basis for personalization. This paper proposes a novel method of personalizing the web-based learning process using data mining. The links and the contents traversed by the learner are identified and analyzed using data mining. The score obtained is also analyzed in order to provide a guideline for the new learners to improve themselves by traversing through the contents through which the successful candidates had traversed. Prediction, an interesting problem in e-learning is applied in this work, although it must be borne in mind that it can easily overlap with classification and regression problems. The forecasting of students’ behavior and performance when using e-learning systems bears the potential of facilitating the improvement of virtual courses as well as e-learning environments in general. Course log-files stored in databases could be mined by trainers using evolutionary algorithms to discover important relationships and patterns, with the target of discovering relationships between learners’ knowledge levels, e-learning system usage times and learners’ scores. This paper proposes a novel method of identifying the interesting patterns by analyzing the learning path taken by the learner along with their interests and goals and the scores obtained with the help of data mining and thereby paving a way to provide an effective learner-centric training. The Data Mining techniques are used for personalizing e-Learning and the results are shown graphically.
||Personalization, e-Learning, Pattern Identification, Data Mining
The International Journal of Learning, Volume 17, Issue 4, pp.585-594.
Article: Print (Spiral Bound).
Article: Electronic (PDF File; 615.206KB).
Assistant Professor (Selection Grade), Computer Applications, Karunya University, Coimbatore, Tamil Nadu, India
Beulah Christalin Latha Christudas is working as an Assistant Professor [S.G.] in the Department of Computer Applications in Karunya University, Coimbatore. She has completed her Masters Degree in Physics and Computer Applications from Madurai Kamaraj University, Madurai. She is currently pursuing her research in the field of E-Learning and Data Mining. She is a life member of Computer Society of India. Her areas of interests include Cloud computing, Web Mining, E-Learning and Text Recognition. Her hobbies include programming, reading, music and gardening.
Associate Professor, Computer Applications, Karunya University, Coimbatore, Tamil Nadu, India
Dr. (Mrs). Sujni Paul obtained her Bachelors degree in Physics from Manonmanium Sundaranar University in 1997 and Masters Degree in Computer Applications from Bharathiar University in the year 2000. She completed her M.Phil during 2004. She has completed her PhD in Data Mining in the Department of Computer Applications, Karunya University, Coimbatore, India in the year 2009. She is working in the area of parallel and distributed data mining. She is working in Karunya University as Associate Professor for the past 8.5 years till date. She has around 4 national and 10 international publications. At present she is guiding 4 Ph.D research scholars and 1 fulltime M.Phil Research scholar.
Deputy General Manager, Bharat Heavy Electricals, Coimbatore, Tamil Nadu, India
Dr. Kirubakaran Ezra obtained B.E (Hons.) degree in Mechanical Engineering, M.E. in Computer Science and Ph.D. in Computer Science from Regional Engineering College, Tiruchirappalli. He obtained his M.B.A. degree from IGNOU. He has more than 30 years of Industrial experience at Bharat Heavy Electricals Ltd. Tiruchirappalli and presetly he is the Senior Deputy General Manager at Bharat Heavy Electricals Ltd., Trichy. He has been a visiting faculty to a number of educational institutions. He had held the posts of Secretary, Vice-Chairman and Chairman of Computer Society of India, Tiruchirappalli. He is a Member of the Syndicate of Bharathidasan University, Member in the Academic Council, Anna University, Trichy and Academic Council, Anna University, Chennai.
Professor & Head, Department of Computer Applications, N.G.P. Institute of Technology, Coimbatore, Tamil Nadu, India
Dr. Saravanan Venkatraman obtained his Bachelors degree in Mathematics from University of Madras during 1996 and Masters Degree in Computer Applications from Bharathiar University during 1999. He has completed his Ph.D. in Computer Science in the Department of Computer Science and Engineering, Bharathiar University in 2004. He is specialized on automated and unified data mining using intelligent agents. His research areas include data warehousing and mining, software agents and cognitive systems. He has presented many research papers in National, International conferences and Journals and also guiding many researchers leading to their PhD degree. He has totally 10 years experience in teaching including 3 years as researcher in Bharathiar University. He is the life member of Computer Society of India, Indian Society for Technical Education, and Indian Association of Research in Computing Sciences and International Association of Computer Science and Information Technology. He worked as Professor and HOD of the Department of Computer Applications in Karunya University, Coimbatore from 1999-2009. At present, he is working as the Director, Computer Applications, Dr. N.G.P. Institute of Technology, Coimbatore.
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