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Abstract
The aim of this research paper is to study the data mining algorithms and its accuracy in prediction. The main objective of this research work is to compare the accuracy of various existing algorithms.. By analyzing and comparing the existing algorithms, this research work tries to suggest a new framework for better prediction. Computer science undergraduate student’s data are collected and analyzed to study the family background, and individual difference factors and their links with their exam performance. Based on the data collected from an arts and Science College, the student’s performance is predicted with various algorithms. The required developments are suggested by introducing the cognitive load factors, personality differences and individual’s prior experiences, etc. From the research it has been observed that the prior experience of the learner’s has positive impact on exam performance. Those who have studied their school education in a particular type of management and practice have more advantage in their exam performance. This prediction of exam performance is due to the prior experience and their similarity in the environment in the same set-ups.