A deep learning model for automated marking of students’ assessments in a learning management system (LMS)

Authors: Mohammed Altamimi ^1, *, Yaser Altameemi ², Adel Alkhalil ³, Romany F. Mansour ⁴, Magdy Abdelrhman ⁵, Ikhlaq Ahmed ⁶, Aakash Ahmad ⁷, Azizah Alogali ^{8, 9}

Affiliations:

¹Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha’il, Ha’il 81481, Saudi Arabia
²Department of English, College of Arts and Literature, University of Ha’il, Ha’il 81481, Saudi Arabia
³Department of Software Engineering, College of Computer Science and Engineering, University of Ha’il, Ha’il 81481, Saudi Arabia
⁴Department of Mathematics, Faculty of Science, New Valley University, El-Kharga 72511, Egypt
⁵Applied College, University of Ha’il, Ha’il, Saudi Arabia
⁶Department of Computer Software Engineering, National University of Sciences and Technology, Islamabad, Pakistan
⁷School of Computing and Communications, Lancaster University Leipzig, Leipzig 04109, Germany
⁸Department of Educational Leadership, University of Rochester, Rochester, NY 14627, USA
⁹Department of Educational Leadership, University of Akron, Akron, OH 44325, USA

Abstract

Learning Management Systems (LMSs) are widely used to support teaching and learning, with platforms such as Blackboard managing lectures, activities, assessments, and reports. Although LMSs provide useful tools and some automated feedback, the accuracy of evaluating students’ typed responses has received little attention in prior research. A particular issue arises in fill-in-the-gap questions, where answers are marked only if they exactly match the instructor’s input, often leading to unfair grading for minor spelling errors. To address this problem, we propose a model that integrates the Levenshtein edit distance with deep learning methods to identify and correct spelling errors, enabling fairer and more accurate automatic grading. The model demonstrated strong performance, achieving an average F1-measure of 0.938 on a dataset of misspelled words.

Keywords

Learning management systems, Automatic grading, Fill-in-the-gap questions, Spelling error correction, Deep learning

Download

📄 Full PDF

DOI

https://doi.org/10.21833/ijaas.2025.10.001

Citation (APA)

Altamimi, M., Altameemi, Y., Alkhalil, A., Mansour, R. F., Abdelrhman, M., Ahmed, I., Ahmad, A., & Alogali, A. (2025). A deep learning model for automated marking of students’ assessments in a learning management system (LMS). International Journal of Advanced and Applied Sciences, 12(10), 1–10. https://doi.org/10.21833/ijaas.2025.10.001