Recommender System for Stimulating the Learning Skill of Slow Learner in Higher Educational Institution using EDM
S. JothiLakshmi1, M.Thangaraj2
1S.Jothi Lakshmi, Asst. Professor, Mannar Thirumalai Naicker College, Madurai, India.
2Dr.M Thangaraj, Professor & Head, Department of Computer Science, School of Information Technology, Madurai Kamaraj University, Madurai, India.
Manuscript received on 12 March 2019 | Revised Manuscript received on 16 March 2019 | Manuscript published on 30 July 2019 | PP: 1962-1966 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1954078219/19©BEIESP | DOI: 10.35940/ijrte.B1954.078219
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© The Authors. 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: Educational data mining is a prominent area to predict the student learning behaviour. A regular analysis of student learning behaviour is used to improve the quality of the academic institution. This paper focuses on the identification of slow learner in the higher educational institution and showing it by educational data mining model. The student performance data from higher educational institution is taken and applied on the classification algorithm using WEKA tool. A recommender system is developed in this research work to stimulate the learning skills of slow learner.
Key words: Data Mining, Classification, Slow Learner, Recommender, EDM.
Scope of the Article: Classification