A Systematic Literature Review on Hybrid Learning Management Systems: Research Gaps and Model Design
DOI:
https://doi.org/10.47709/ijmdsa.v4i4.7441Keywords:
hybrid lms, system integration, usability, user experience, learning effectivenessAbstract
This study aims to systematically examine literature related to the development of hybrid Learning Management Systems (LMS), focusing on system integration models, cross-platform usability aspects, and their effectiveness in supporting student engagement and learning outcomes. The review was conducted using a Systematic Literature Review (SLR) approach following the PRISMA 2020 guidelines. Out of a total of 1,342 identified publications, 25 studies met the inclusion criteria and were analyzed further.The synthesis results indicate that hybrid LMS integration is still largely dominated by technical approaches, such as the use of APIs, interoperability standards, and hybrid recommendation systems. However, most studies have not yet fully incorporated pedagogical principles into the system design. Usability analysis reveals that web platforms tend to be more capable of supporting complex learning activities, while mobile platforms offer flexibility but are limited by deeper navigation structures and interface consistency challenges.In terms of effectiveness, several studies reported increased engagement and support for adaptive learning, although empirical evidence regarding impacts on learning outcomes remains limited. Overall, the success of hybrid LMS depends on alignment between technical integration, UX design, and pedagogical needs. Future research is recommended to develop and evaluate hybrid LMS prototypes that meaningfully integrate structured and self-directed learning, conduct in-depth cross-platform usability evaluations, and explore hybrid LMS models that incorporate artificial intelligence (AI) as an adaptive component within the learning process.
References
Abdulquadir, A. A., Abdulsalam, O., Mcmahon, R., & Prabhakar, A. (2023). Usability Study of a Learning Management System (LMS). Proceedings of the 24th Annual Conference on Information Technology Education, 150–156. https://doi.org/10.1145/3585059.3611415
Abid, A., Tufail, A. H., Salem, O. M. A., Nawaz, N. A., Farooq, U., Abid, I., & Ishaq, K. (2024). An evaluation framework and comparative analysis of the widely used learning management systems. PLoS ONE, 19(12 December), 1–30. https://doi.org/10.1371/journal.pone.0311111
Alkoblan, S. I., & Wadud, M. A.-A. (2023). A Model for Usability Evaluation of Learning Management Systems. International Journal on Integrating Technology in Education, 12(1), 59–71. https://doi.org/10.5121/ijite.2023.12105
Aucancela, M., Briones, A. G., & Chamoso, P. (2023). Educational Recommender Systems: A Systematic Literature Review. The Barcelona Conference on Education 2023: Official Conference Proceedings, March, 933–951. https://doi.org/10.22492/issn.2435-9467.2023.74
Bergdahl, N., Bond, M., Sjöberg, J., Dougherty, M., & Oxley, E. (2024). Unpacking student engagement in higher education learning analytics: a systematic review. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-024-00493-y
Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3(January), 100068. https://doi.org/10.1016/j.caeai.2022.100068
Butmeh, H., & Abu-Issa, A. (2024). Hybrid attribute-based recommender system for personalized e-learning with emphasis on cold start problem. Frontiers in Computer Science, 6. https://doi.org/10.3389/fcomp.2024.1404391
Chen, F. (2025). Learning analytics in inquiry-based learning: a systematic review. In Educational Technology Research and Development (Vol. 73, Issue 4). Springer US. https://doi.org/10.1007/s11423-025-10507-9
da Silva, F. L., Slodkowski, B. K., & & Cazella, S. C. (2023). A systematic literature review on educational recommender systems for teaching and learning?: research trends , limitations and opportunities. In Education and Information Technologies. Springer US. https://doi.org/10.1007/s10639-022-11341-9
Gumasing, M. J. J., Vasquez, A. B., Doctora, A. L. S., & Perez, W. D. D. (2022). Usability Evaluation of Online Learning Management System: Comparison between Blackboard and Canvas. Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe), 25–31. https://doi.org/10.1145/3523132.3523137
Heathen, T. S. (2025). Learning Management Systems for Hybrid Learning?: The New Trend Learning Management Systems for Hybrid Learning?: The New Trend. 0–6. https://doi.org/10.20944/preprints202503.0026.v2
Ikhsan, I., Hartanti, K., & Lopo, F. L. (2025). Strategies for Implementing AI in LMS to Improve the Effectiveness and Personalization of Digital Learning. The Journal of Academic Science, 2(3), 944–953. https://doi.org/10.59613/qp3e7d30
Kaliisa, R., Misiejuk, K., López-Pernas, S., Khalil, M., & Saqr, M. (2024). Have Learning Analytics Dashboards Lived Up to the Hype? A Systematic Review of Impact on Students’ Achievement, Motivation, Participation and Attitude. ACM International Conference Proceeding Series, 295–304. https://doi.org/10.1145/3636555.3636884
Khanal, S., & Pokhrel, S. R. (2024). Analysis, Modeling and Design of Personalized Digital Learning Environment. 1–9. http://arxiv.org/abs/2405.10476
Kurniawan Malik Ibrahim, Ati Suci Dian Martha, & Dawam Dwi Jatmiko Suwawi. (2023). Implementation of the Learner Centered Design method and the personality approach (Case Study: Redesigning The Interface mobile LMS Tel-U). International Journal on Information and Communication Technology (IJoICT), 9(1), 57–72. https://doi.org/10.21108/ijoict.v9i1.723
Lampropoulos, G. (2023). Recommender systems in education: A literature review and bibliometric analysis. Advances in Mobile Learning Educational Research, 3(2), 829–850. https://doi.org/10.25082/amler.2023.02.011
Maruyama, M. H. M., Silveira, L. W., de Oliveira, J. P. M., Gasparini, I., & Maran, V. (2023). Hybrid Recommender System for Educational Resources to the Smart University Campus Domain. International Conference on Computer Supported Education, CSEDU - Proceedings, 1(Csedu), 47–56. https://doi.org/10.5220/0011841900003470
Molinari, A., & Sandri, S. (2024). Evolution of LMS Design and Implementation in the Age of AI and Large Language Models. CEUR Workshop Proceedings, 3879.
Ngulube, P., & Ncube, M. M. (2025). Leveraging Learning Analytics to Improve the User Experience of Learning Management Systems in Higher Education Institutions. Information (Switzerland), 16(5), 1–20. https://doi.org/10.3390/info16050419
Page, M. J., Mckenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-wilson, E., Mcdonald, S., … Moher, D. (2021). The PRISMA 2020 statement?: an updated guideline for reporting systematic reviews Systematic reviews and Meta-Analyses. https://doi.org/10.1136/bmj.n71
Pal, N., & Dahiya, O. (2023). A Systematic Literature Review on the Implications of Educational Recommender System in Teaching Learning Environment. International Journal of Engineering Trends and Technology, 71(4), 203–212. https://doi.org/10.14445/22315381/IJETT-V71I4P218
Pan, Z., Biegley, L., Taylor, A., & Zheng, H. (2024). A Systematic Review of Learning Analytics– Incorporated Instructional Interventions on Learning Management Systems. Journal of Learning Analytics, 11(2), 52–72. https://doi.org/10.18608/jla.2023.8093
Paolucci, C., Vancini, S., Bex, R. T., Cavanaugh, C., Salama, C., & de Araujo, Z. (2024). A review of learning analytics opportunities and challenges for K-12 education. Heliyon, 10(4), e25767. https://doi.org/10.1016/j.heliyon.2024.e25767
Petrovic, T., & Alvarez, R. (2025). AI-Driven Content Recommendation in Learning Management Systems (LMS): A Hybrid Filtering Approach. International Academic Journal of Science and Engineering, 12(3), 20–24. https://doi.org/10.71086/iajse/v12i2/iajse1213
Siafis, V., Rangoussi, M., & Psaromiligkos, Y. (2024). Recommender Systems for Teachers: A Systematic Literature Review of Recent (2011–2023) Research. Education Sciences, 14(7). https://doi.org/10.3390/educsci14070723
Williams, D. (2022). Improving User Experience in Learning Management Systems Improving User Experience in Learning Management Systems.
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