Predicting student next-term performance in degree programs using AI-based approach: a case study from Ghana

Predicting student next-term performance in degree programs using AI-based approach: a case study from Ghana

Student performance can fluctuate over time due to various factors (e.g. previous assignment grades, social life and economic conditions). Temporal dynamics, such as semester-to-semester variations and changes in students’ academic achievements, behaviors and engagement over time, can be critical fa...

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Bibliographic Details
Main Authors: John-Bosco Diekuu, M. S. Mekala, Ulric Sena Abonie, John Isaacs, Eyad Elyan
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Cogent Education
Subjects:
AI in Education
higher education
next-term performance
machine learning
LSTMs architecture
Artificial Intelligence
Online Access:https://www.tandfonline.com/doi/10.1080/2331186X.2025.2481000
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https://www.tandfonline.com/doi/10.1080/2331186X.2025.2481000

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