Educational Data Mining Approaches for Predicting Student Performance and Retention
DETAILS
Call for Papers
Educational Data Mining Approaches for Predicting Student Performance and Retention
Journal: Africa Education Review
Publisher: Taylor & Francis
Manuscript Submission Deadline: 11 November 2026
Africa Education Review invites submissions for its Special Issue on Educational Data Mining Approaches for Predicting Student Performance and Retention.
About the Special Issue
Educational Data Mining (EDM) is transforming how institutions identify students at risk and improve academic success through data-driven decision-making. By leveraging machine learning, deep learning, and explainable AI techniques, educators can analyze academic performance, learning behaviors, and engagement patterns to develop timely interventions that enhance student retention and learning outcomes.
This Special Issue seeks high-quality research exploring innovative EDM methodologies for predicting student performance, supporting personalized learning, improving curriculum design, and strengthening institutional strategies for student success. Contributions that demonstrate practical applications of predictive analytics and intelligent educational systems are particularly encouraged.
Topics of Interest
Submissions may include, but are not limited to:
Educational Data Mining (EDM)
Student performance prediction
Student retention and early warning systems
Machine learning in education
Deep learning applications for education
Classification, regression, and clustering techniques
Explainable Artificial Intelligence (XAI)
Ensemble learning models
Learning analytics and engagement analysis
Curriculum improvement through data analytics
Personalized learning and intervention strategies
Data-driven educational decision-making
Preferred Article Types
The journal welcomes:
Original Research Articles
Empirical Studies
Quantitative Research
Qualitative Research
Mixed-Methods Studies
Applied Data Analytics Research
Submission Information
Manuscript Submission Deadline: 11 November 2026
Manuscripts must be submitted through the journal's online submission system.
Authors should follow the journal's official Instructions for Authors before submission.
All submissions must be original, unpublished, and not under consideration by another journal.
Special Issue Editors
Dr. Adebukola Onashoga, Federal University of Agriculture, Nigeria
Dr. Adebayo Abayomi-Alli, INESC TEC & University of Porto, Portugal
Dr. Vivian Ogochukwu Nwaocha, National Open University of Nigeria, Nigeria
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