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Education and Information Technologies

Erschienen in:

25.06.2019

A machine learning algorithm framework for predicting students performance: A case study of baccalaureate students in Morocco

verfasst von: Aimad Qazdar, Brahim Er-Raha, Chihab Cherkaoui, Driss Mammass

Erschienen in: Education and Information Technologies | Ausgabe 6/2019

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Abstract

The use of machine learning with educational data mining (EDM) to predict learner performance has always been an important research area. Predicting academic results is one of the solutions that aims to monitor the progress of students and anticipates students at risk of failing the academic pathways. In this paper, we present a framework for predicting student performance based on Machine Learning algorithm at H.E.K high school in Morocco from 2016 to 2018. The proposed model was analyzed and tested using student’s data collected from The School Management System “MASSAR” (SMS-MASSAR). The dataset used in this study concerns 478 Physics students during the school years: 2015–2016, 2016–2017 and 2017–2018. The predictive performance results showed that our model can make more precise predictions of student’s performance.

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Titel: A machine learning algorithm framework for predicting students performance: A case study of baccalaureate students in Morocco
verfasst von: Aimad Qazdar
Brahim Er-Raha
Chihab Cherkaoui
Driss Mammass
Publikationsdatum: 25.06.2019
Verlag: Springer US
Erschienen in: Education and Information Technologies / Ausgabe 6/2019
Print ISSN: 1360-2357
Elektronische ISSN: 1573-7608
DOI: https://doi.org/10.1007/s10639-019-09946-8

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