[ Prédiction de la probabilité de réussite en sciences informatiques et orientation départementale ]
Volume 77, Issue 1, February 2025, Pages 129–138



Mavuela Maniansa Richard1
1 Institut Supérieur Pédagogique et Techniques de Kinshasa, RD Congo
Original language: French
Copyright © 2025 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Through an observation of student’s performance in computer science, we want to reveal that the factors influencing success can be identified and modeled using advanced machine learning techniques.
Author Keywords: Orientation, predictive modeling, data analysis.
Volume 77, Issue 1, February 2025, Pages 129–138




Mavuela Maniansa Richard1
1 Institut Supérieur Pédagogique et Techniques de Kinshasa, RD Congo
Original language: French
Copyright © 2025 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Through an observation of student’s performance in computer science, we want to reveal that the factors influencing success can be identified and modeled using advanced machine learning techniques.
Author Keywords: Orientation, predictive modeling, data analysis.
Abstract: (french)
A travers une observation de la performance des étudiants en sciences informatiques, nous voulons révéler que les facteurs y influençant la réussite peuvent être identifiés et modélisés grâce aux techniques avancées de l’apprentissage automatique.
Author Keywords: Orientation, modélisation prédictive, analyse des données.
How to Cite this Article
Mavuela Maniansa Richard, “Prediction of the probability of success in computer science and departmental orientation,” International Journal of Innovation and Scientific Research, vol. 77, no. 1, pp. 129–138, February 2025.