doi: 10.18178/ijiet.2026.16.6.2615
Investigating the Integration of Artificial Intelligence in Learning Assessment: Towards an Automated Remediation
Siham Guenboura*
,
Khalid El Khattabi ,
Fatima Ouzennou ,
Hamza Fakhar
- Center for Doctoral Studies, Sciences, Technologies, and Medical Sciences, Laboratory for Scientific Innovation in Sustainability, Environment, Education, and Health in the Era of Artificial Intelligence (LISDEESIA), Ecole Normale Supérieure (ENS) Sidi Mohamed Ben Abdellah University, Bensouda Fez, Morocco
- Manuscript receivedAugust 5, 2025
- revisedSeptember 15, 2025
- acceptedNovember 28, 2025
- publishedJune 11, 2026
Abstract
In the context of educational innovation, Artificial Intelligence (AI) is transforming assessment and remediation, fostering greater personalization and efficiency. This study explores teachers’ perceptions and practices in assessment and remediation, as well as their views on AI’s potential to support adaptive interventions. A questionnaire was administered to 210 secondary school physics and chemistry teachers in the Fès-Meknès region. Findings show that diagnostic, formative and summative assessments are widely used, but challenges such as low student motivation, time constraints, and diverse learner needs limit assessment practices overall. Digital tools remain underused, with traditional methods still prevailing. While most teachers implement remediation, they struggle to adapt it to individual learners. Notably, 77.6% of respondents express a positive view of AI’s potential, particularly for personalized learning, adaptive testing, and automated reporting. These results provide an overview of current practices and highlight the significant opportunities AI offers for improving the effectiveness and adaptability of assessment and remediation strategies.
Keywords
- artificial intelligence
- assessment
- remediation
- adaptive learning
- e-learning
- physics/chemistry teachers
How to Cite
Siham Guenboura, Khalid El Khattabi, Fatima Ouzennou, and Hamza Fakhar, "Investigating the Integration of Artificial Intelligence in Learning Assessment: Towards an Automated Remediation," International Journal of Information and Education Technology, vol. 16, no. 6, pp. 1494-1504, 2026. https://doi.org/10.18178/ijiet.2026.16.6.2615
Copyright & License
Copyright © 2026 by the authors. 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 (CC BY 4.0).