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Survey Paper | Information Technology | India | Volume 3 Issue 12, December 2014

Survey Report on: EDM for Prediction of Academic Trends & Patterns

Trupti S. Diwan | Bharati Dixit ^[2]

Abstract: Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of datasets. This paper surveys the two elements needed to make prediction on Students Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of Students Academic Performance in Higher Learning Institute.

Keywords: Classification, Educational data mining, Student failure, Grammar-based genetic programming

Edition: Volume 3 Issue 12, December 2014,

Pages: 610 - 612