International Journal of Education and Information Technologies

     
E-ISSN: 2074-1316
Volume 15, 2021

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

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Volume 15, 2021

Title of the Paper: Using Machine Learning for Prediction Students Failure in Morocco: An Application of the CRISP-DM Methodology

Authors: Nada Lebkiri, Mohamed Daoudi, Zakaria Abidli, Joumana Elturk, Abdelmajid Soulaymani, Youssef Khatori, Youssef El Madhi, Mohammed Benattou

Pages: 344-352 

DOI: 10.46300/9109.2021.15.36     XML

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Abstract: Student failure prediction is one of the main topics in university learning contexts, as it helps to avoid failure in higher education institutions and provides a basis to make the teaching and learning process more effective, efficient and reliable. The overall aim of this study is to identify students who are susceptible to fail a given university course. This research paper reports the implementation of an Educational Data Mining project based on the CRISP-DM methodology. The data was collected from the APOGEE system of Ibn Tofail University, a form and specifications of the tested courses. The business goal of this paper is to develop a model that can identify students who are susceptible to failure in a given academic course. Such a model helps prevent failure in higher education institutions and provides a basis for making the teaching and learning process more effective, efficient and reliable. Most common machine learning algorithms in the field of Educational Data Mining were used. The results of our research showed that the proposed method was able to achieve an overall accuracy of 97% in predicting students at potential failure.

Citation: Nada Lebkiri, Mohamed Daoudi, Zakaria Abidli, Joumana Elturk, Abdelmajid Soulaymani, Youssef Khatori, Youssef El Madhi, Mohammed Benattou, Using Machine Learning for Prediction Students Failure in Morocco: An Application of the CRISP-DM Methodology, pp. 344-352, Volume 15, 2021, International Journal of Education and Information Technologies (NAUN). DOI: 10.46300/9109.2021.15.36.