Recent Submissions

• Loading...

  8

  19

  Item type:Item, Add to my list

  Explainable AI for Early Prediction of Student Academic Success Using Learning Behaviour Analytics

  (2026-07-01) Sani Abubakar

  Show more

  The increasing availability of digital learning platforms has created opportunities to identify students who may experience academic difficulties before poor outcomes become evident. Learning management systems continuously generate behavioural traces, including login activity, assessment participation, assignment submission patterns, resource engagement, and interaction with course materials. When systematically analysed, these behavioural indicators can provide valuable signals for the early prediction of student academic success. However, conventional machine-learning approaches often provide predictions without sufficiently explaining the factors responsible for those predictions, limiting their usefulness and acceptance among educators. This study proposes an explainable artificial intelligence framework for the early prediction of student academic success using learning behaviour analytics. The framework integrates behavioural data preprocessing, temporal feature engineering, machine-learning classification, and explainable AI techniques to generate both outcome predictions and interpretable explanations. Multiple predictive models are considered to examine their ability to distinguish students according to their expected academic outcomes at progressively earlier stages of the learning period. Explainability techniques are subsequently employed to identify the behavioural characteristics that contribute most strongly to model predictions at both global and individual levels. The proposed approach is intended to move beyond prediction alone by providing educators with actionable information about the behavioural patterns associated with academic risk or success. By examining prediction performance across different points in the learning process, the study also addresses the practical question of how early reliable intervention signals can be generated. The resulting framework provides a transparent foundation for data-informed academic support while highlighting the importance of interpretability, responsible use of student data, and timely educational intervention.

  Show more
• Loading...

  7

  18

  Item type:Publication, Add to my list

  La dernière époque du commerce transsaharien au Sahara central (1850-1910): De l’implication ottomane aux massacres français

  (Institut de Recherches en Sciences Humaines - IRSH, 2026-07-30) Duymus, Kerem

  Show more

  La littérature de recherche sur le commerce transsaharien dans le Sahara central au XIXe siècle a longtemps été fondée sur les comptes des voyageurs européens. Cela a conduit à une narration problématique concernant ses principales dynamiques et son déclin supposé, car ceux-ci n'avaient pas accès à la connaissance appropriée de la région et se sont simplement suivis d'un point de vue impérialiste et colonialiste. Des nouvelles sources en arabe et turque, ainsi que des documents archivés provenant de Libye et de Turquie grandement dérangent ces récits eurocentriques. Les nouveaux découvertes illustrent un dynamisme complètement différent pour le commerce transsaharien, tandis qu'elles mettent aussi en question le déclin supposé de celle-ci. De plus, les nouvelles découvertes révèlent la nature des engagements des Ottomans et français à partir de 1850, qui ont joué un rôle crucial dans la détermination du cours des affaires commerciales. Or, l'Empire ottoman s'est appuyé sur le commerce transsaharien, tandis que la France a mené des attaques contre les marchands civils pour briser cette traque. Finalement, la France atteignait son objectif uniquement en 1906 après avoir tué plus de mille marchands civils.

  Show more