IJIET 2025 Vol.15(11): 2511-2517
doi: 10.18178/ijiet.2025.15.11.2446
doi: 10.18178/ijiet.2025.15.11.2446
Exploring Student Expectations and Preferences Regarding Online Adaptive Revision: Implications for the Successful Design of Personalized Learning Systems
Kaoutar Smahi*, Ouidad Labouidya, and Khalid El Khadiri
Laboratory of Sciences and Technologies of Information and Communication, Faculty of Science, Chouaib Doukkali University, El
Jadida, Morocco
Email: Smahi.k@ucd.ac.ma (K.S.); labouidya.o@ucd.ac.ma (O.L.); khalid.elkhadiri@ucd.ac.ma (K.E.K.)
*Corresponding author
Email: Smahi.k@ucd.ac.ma (K.S.); labouidya.o@ucd.ac.ma (O.L.); khalid.elkhadiri@ucd.ac.ma (K.E.K.)
*Corresponding author
Manuscript received June 17, 2025; revised July 14, 2025; accepted August 21, 2025; published November 19, 2025
Abstract—To better understand students’ needs regarding personalized revision, we explored their expectations of adaptive learning and evaluated their experiences with flipped learning throughout a semester. This study builds upon previous research that identified Moodle as the most effective online assessment platform, with the goal of developing an Personalized Exam Revision (PER) plug-in for Moodle. By integrating theoretical frameworks such as Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), DeLone and McLean, as well as the Kano model, we developed a unique conceptual model that guided the design of our questionnaire. We then analyzed survey data gathered from students at Chouaib Doukkali University. Adopting an original mixed-methods approach we integrated Principal Component Analysis (PCA), followed by the K-means clustering algorithm to optimise the separation of groups, as well as Natural Language Processing (NLP), to derive meaningful insights from the data. The findings provide valuable insights into students’ requirements, preferences, and satisfaction levels, as well as the impact of Moodle on their learning process. Based on these results, we propose strategic recommendations for developing an adaptive revision module that aligns with students’ actual needs, ensuring that our Moodle plug-in is developed in the right direction to effectively enhance the assessment process.
Keywords—adaptative learning, Personalized Exam Revision (PER), online assessment, Unified Theory of Acceptance and Use of Technology (UTAUT), Kano’s model, Natural Language Processing (NLP), K-means
Copyright © 2025 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).
Keywords—adaptative learning, Personalized Exam Revision (PER), online assessment, Unified Theory of Acceptance and Use of Technology (UTAUT), Kano’s model, Natural Language Processing (NLP), K-means
Cite: Kaoutar Smahi, Ouidad Labouidya, and Khalid El Khadiri, "Exploring Student Expectations and Preferences Regarding Online Adaptive Revision: Implications for the Successful Design of Personalized Learning Systems," International Journal of Information and Education Technology, vol. 15, no. 11, pp. 2511-2517, 2025.
Copyright © 2025 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).