An intelligent system to predict academic performance based on different factors during adolescence

ABSTRACT Students need to have an effective education to take advantage of all the latest tools available. Even with a proper education, they are failing to reap its benefits; reasons involve social, economic and psychological factors a student faces during their adolescence. Our research is directed towards this particular problem of educational effectiveness. We have surveyed a large number of students across different districts in Bangladesh. Pre-processing was done thoroughly; the use of data balancing, dimensionality reduction, discretization and normalization in combinations has allowed us to derive the best model that could predict the academic performance based on different factors during the adolescence.

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