STI Laboratory, IDM, T-IDMS Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, Morocco
STI Laboratory, IDM, T-IDMS Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, Morocco
Ecole Nationale de Commerce et de Gestion, Moulay Ismail University of Meknes, Morocco
This paper aims to conceptualize, design, and implement a Data Mining (DM) system integrated with machine learning within the realm of school management. The primary objective is to support the educational community and decision-makers in addressing the issue of school dropout and enhancing success rates at the certificate levels in Morocco, specifically focusing on the bachelor's degree examination in the qualifying cycle. The proposed system categorizes students five months prior to the exam date, facilitating targeted academic interventions for those at risk of course repetition or discontinuation. The DM system, operational throughout the school year, enhances the precision and effectiveness of schools and provincial administrations by identifying areas requiring additional support to improve end-of-year success rates and student performance. Project development is rooted in the collection and analysis of existing data from various departmental information systems, utilizing classification and regression algorithms to predict learner performance, success rates, and overall outcomes at the conclusion of certificate levels.
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