Open AccessPredicting Academic Performance of Tertiary Students using Classification Algorithm
Author(s) -
S. Jayaprakash,
Jaiganesh V.
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b2716.078219
Subject(s) - benchmark (surveying) , institution , entertainment , computer science , field (mathematics) , gauge (firearms) , academic institution , machine learning , tertiary institution , recommender system , algorithm , higher education , tertiary level , mathematics education , artificial intelligence , medical education , psychology , mathematics , sociology , social science , political science , medicine , library science , geodesy , archaeology , pure mathematics , law , history , geography
Classification algorithms have paved the way for several recommender systems in the field of Medicine, Entertainment, Politics, Education, etc. Recently there is a growing interest among researchers to analyze or predict the academic progression of students from High Schools to Tertiary Education. Better performance of students will directly reciprocate in the growth of an institution. Hence, setting up a supervised learning system will act as a gauge to provide a benchmark education. This paper aims to recommend a system based on a predictive model which will aid the institution to measure the performance of students based on various parameters.