Manuscript received February 8, 2023; revised March 17, 2023; accepted May 12, 2023.
Abstract—This article presents the development and
evaluation of a computer-assisted language learning system
designed for self-training in scientific French language. The
main problem addressed by this research is the linguistic
obstacles faced by students during their academic years, which
inspired the implementation of an adaptive learning system
personalized to their needs. The methodology applied involved a
need analysis approach to better adapt the French language
learning offer to students’ demand, followed by the development
of an adaptive learning model based on Item Response Theory
(IRT). The system was evaluated by the System Usability Scale
(SUS) model which shows high usability and user satisfaction
and engagement. The findings were very encouraging,
demonstrating that the presented adaptive learning model
improves the adaptability of students’ needs and preferences.
Overall, the aim of this research is to prove that the proposed
learning system will improve the learners’ performance and
understanding of scientific French language.
Index Terms—Self-training, personalization, adaptive
learning, item response theory, adaptive spacing system
S. Ouald Chaib, I. Joti, and S. Khoulji are with the National School of
Applied Sciences, Tetouan, University Abdelmalek Essaadi, Morocco.
*Correspondence: sara.oualdchaib@etu.uae.ac.ma (S.O.C.)
Cite: Sara Ouald Chaib*, Imane Joti, and Samira Khoulji, "Evaluation of a Computer-Assisted Language Learning System Based on Adaptive Learning Designed for Self-training in Scientific French Language," International Journal of Information and Education Technology vol. 13, no. 8, pp. 1284-1296, 2023.
Copyright © 2023 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).