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Home > Archives > Volume 20, No 12 (2022) > Article

DOI: 10.14704/nq.2022.20.12.NQ77002

Analysis Of Students Performance Prediction in Online Courses Using Machine Learning Algorithms

Sachin S. Bere, Ganesh P. Shukla, Vajid N Khan, Atishkumar M. Shah, Dattatray G. Takale


An enormous measure of computerized information is being produced over a wide assortment in the field of data mining strategies. The creation of student achievement prediction models to predict student performance in academic institutions is a key area of the development of Education Data Mining. A prediction system has been proposed by using state universities of Maharashtra and Students previous semester marks. The study is evaluated using Random Forest (RF), MultiLayer Perceptron (MLP) and k-Nearest Neighbour (KNN). In order to attain their higher score, this framework would assist the student to recognize their final grade and improve their academic conduct.


Open University Learning Analytics Dataset (OULAD), Machine learning, Decision tree, KNN

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