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Application of Predictive Analytics in Intelligent Course Recommendation

Publication Type : Conference Paper

Thematic Areas : Amrita e-Learning Research Lab

Publisher : Procedia Computer Science

Source : Procedia Computer Science, Elsevier, Volume 93, p.917-923 (2016)

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Keywords : Apriori principle, Cognitive ability, course choice, decision paralyses, Education, Forecasting, Legacy data, Students

Campus : Amritapuri

School : School of Engineering

Center : E-Learning

Department : E-Learning

Year : 2016

Abstract : Students who pursue admission to colleges usually experience a difficulty to select a course. In this paper, we propose a course recommendation system to find out the courses which are apt for a student pursuing admission to the college. Typically, the prediction is based on the career goal or the present job trend. In this system proposed, the prediction is formulated based on the grades acquired by the student in twelfth standard; which is taken as a sign of the previous academic performance and cognitive ability of the student. A model is generated from the legacy data or data from the students who have completed the course successfully. This model is used for predicting the courses for new students. The idea behind this approach is that when a student with specific set of skills is successful in a course then another student with similar set of skills will have a higher success probability in the said course.

Cite this Research Publication : D. Upendran, Chatterjee, S., Sindhumol, S., Kamal Bijlani, J, M., and J., J., “Application of Predictive Analytics in Intelligent Course Recommendation”, in Procedia Computer Science, 2016, vol. 93, pp. 917-923.

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