A Systematic Literature Review of Explainable Artificial Intelligence (XAI) for Interpreting Student Performance Prediction in Computer Science and STEM Education
Open Access
- 13 June 2025
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 221-227
Abstract
No abstract availableFunding Information
- FCT - Fundação para a Ciência e a Tecnologia, I.P. (UIDB/00326/2025 and UIDP/00326/2025)
This publication has 31 references indexed in Scilit:
- Explainable Artificial Intelligence in Education: A Comprehensive Review2023
- Earliest Possible Global and Local Interpretation of Students’ Performance in Virtual Learning Environment by Leveraging Explainable AIIEEE Access, 2022
- Early prediction of learners at risk in self-paced education: A neural network approachExpert Systems with Applications, 2022
- Perspectives on the challenges of generalizability, transparency and ethics in predictive learning analyticsComputers and Education Open, 2021
- Explainable artificial intelligence: a comprehensive reviewArtificial Intelligence Review, 2021
- Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive ModelIEEE Access, 2021
- A deep learning classification framework for early prediction of team-based academic performanceApplied Soft Computing, 2021
- Generation of Automatic Data-Driven Feedback to Students Using Explainable Machine Learning2021
- Interpretable Clustering of Students’ Solutions in Introductory Programming2021
- Permutation importance: a corrected feature importance measureBioinformatics, 2010