Framework for Predicting Students’ Performance–Review of Techniques
DOI:
https://doi.org/10.17010/ijcs/2017/v2/i2/112040Keywords:
Student Performance Prediction
, Classification Methods, Rule-Based Classification, Regression Methods, Data-MiningManuscript received January 20
, 2017, revised March 8, accepted March 9, 2017. Date of publication April 5, 2017.Abstract
With the advent of self-funding institutions in the education sector, retaining students along all the semesters of the academic program in order to maintain the desired cash-flow through re-registration has become a major challenge. A common tendency of students is discontinuing a course if they fail in any subject. Hence, predicting students' probable performance in semester-end examination and helping them raise performance level by providing necessary guidance have become the need of the day. Many research works have been directed towards this area. This paper attempted to provide a comprehensive review of all major researches that have been undertaken for prediction of student performance. It also attempted to suggest a common framework which can be used in studies related to student performance prediction. This framework can be used for predicting student performance on the basis of availability of relevant student data.Downloads
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