S. JothiLakshmi,M. Thangaraj,



Data mining,classification mining,collaborative recommendation,course selection,EDM,


In a higher education system, student faces a difficulty in choosing a right course from the large pool of courses in the institution. The course recommender framework provides necessary guidance to student network to choose a course in their scholarly schedule. This paper explores the potential of Educational data mining for course selection recommendation by predicting student’s course selection which involves analysing admission data of student in the institution. The proposed framework was designed as agent based recommender system to improve the efficiency of recommendations. There are three agents in this model, Pattern discovery agent generates the course selection pattern which is filtered by filtering agent. The recommendation agent provides recommendation. The proposed model was analyzed and tested using admission data collected from the higher educational institution. More specifically the model is applied on 10000 student admission data in the distance learning programme. The model is evaluated by three experiments, the experimental results indicates that this recommender system can more accurate predictions of course selections.


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