ADAPTIVE LEARNING SYSTEMS FOR LANGUAGE PROFICIENCY DEVELOPMENT IN HIGHER EDUCATION: A SYSTEMATIC LITERATURE REVIEW
Keywords:
adaptive learning systems, language proficiency, higher education, personalized learning, educational technologyAbstract
The growing demand for personalized and data-driven instruction in higher education has spurred interest in adaptive learning systems as a transformative approach to language education. This systematic literature review investigates how adaptive learning systems contribute to language proficiency development in tertiary institutions. Guided by established review protocols, peer-reviewed studies published between 2015 and 2025 were analyzed across major academic databases, focusing on empirical and conceptual works addressing adaptive learning in language teaching and learning contexts. Findings revealed that adaptive learning systems enhance learners’ proficiency by providing individualized feedback, data-informed content sequencing, and real-time progress tracking. These systems support diverse linguistic competencies in grammar, vocabulary, reading comprehension, and oral communication, through artificial intelligence and learning analytics, particularly for grammar, vocabulary, reading comprehension, and oral communication. The review identifies several pedagogical frameworks, including constructivist and personalized learning models, as central to the design and implementation of adaptive technologies in language classrooms. However, challenges such as technological limitations, limited instructor readiness, and data privacy issues persist. The study concludes that adaptive learning systems hold significant potential for advancing language proficiency in higher education by aligning instruction with learners’ unique needs and learning trajectories. It recommends increased institutional support, professional training, and integration of pedagogically grounded adaptive systems to achieve more inclusive, efficient, and sustainable language learning outcomes.References
Adedoja, G., Botha, A., & Ogunniyi, M. B. (2013). The development of a web-based collaborative learning environment for enhancing students’ learning in Nigeria. Computers & Education, 69, 521–531. https://doi.org/10.1016/j.compedu.2013.07.020
Afolabi, A. O. (2015). E-learning and its effects on teaching and learning in a global age. International Journal of Academic Research in Business and Social Sciences, 5(1), 203–210.
Alrakhawi, H. A. (2023). Intelligent Tutoring Systems in Education: systematic literature review. Journal of Applied and Theoretical Information Technology. jatit.org
Contrino, M. F., et al. (2024). Using an adaptive learning tool to improve student outcomes in university courses (CogBooks implementation). Smart Learning Environments. Springer Open.
Dada, S. (2024). Use of an intelligent tutoring system for a curriculum on AAC: development and effectiveness. University of Pretoria repository.
du Plooy, E. (2024). Personalized adaptive learning in higher education: scoping review of key characteristics and impact. ScienceDirect / regional journal.
Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12), 1216. https://doi.org/10.3390/educsci13121216
Guo, L., Wang, D., Gu, F., Li, Y., Wang, Y., & Zhou, R. (2021). Evolution and trends in intelligent tutoring systems research: a multidisciplinary and scientometric view. Asia Pacifc Education Review, 22 (3), 441–461 https://doi.org/10.1007/s12564-021-09697-7
Huang, Y. (2023). Supporting skill integration in an intelligent tutoring system: instructional design and empirical evaluation. Journal of Computer Assisted Learning. Wiley. Wiley Online Library.
Katsaris, I., & Vidakis, N. (2021). Adaptive e-learning systems through learning styles. A review of the literature. Advances in Mobile Learning Educational Research · https://doi.org/10.25082/AMLER.2021.02.007
Kabudi, T., Pappas, I., & Olsen, D. H. (2021). AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers & Education: Artificial Intelligence, 2, Article 100017. https://doi.org/10.1016/j.caeai.2021.100017.
Kaur, P., Kumar, H., & Kaushal, S. (2023). Technology-assisted language learning adaptive systems: A comprehensive review. International Journal of Cognitive Computing in Engineering, 4, 301–313. https://doi.org/10.1016/j.ijcce.2023.09.002. OUCI
Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta- analytic review. Review of Educational Research.
https://doi.org/10.3102/0034654315581420.
Martin, F., Chen, Y., Moore, R. L., & Westine, C. D. (2020). Systematic review of adaptive learning research designs, context, strategies, and technologies from 2009 to 2018. Educational Technology Research and Development, 68(4), 1903–1929. https://doi.org/10.1007/s11423-020-09793-2.
Mirata, V., & colleagues. (2020). Challenges and contexts in establishing adaptive learning in higher education: Findings from a Delphi study. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-020-00209-y.
Ololube, N. P. (2006). Appraising the relationship between ICT usage and integration and the standard of teacher education programs in Nigeria. International Journal of Education and Development using ICT, 2(3), 70–85.
Ololube, N. P. (2011). Education and technology in the 21st century. Springer. https://doi.org/10.1007/978-94-007-2326-3
Ogunleye, O. S. (2010). Analysis of the use of information and communication technology for gender empowerment and sustainable poverty alleviation in Nigeria. International Journal of Education and Development using ICT, 6(3), 5–17.
Oye, N. D., Iahad, N. A., & Rahim, N. Z. A. (2012). The history of UTAUT model and its impact on ICT acceptance and usage by academicians. Education and Information Technologies, 19(1), 251–270. https://doi.org/10.1007/s10639-012-9189-9
Shadiev, R., & Wang, X. (2022). A review of research on technology-supported language
learning and 21st century skills. Frontiers in Psychology, 13, Article 897689. https://doi.org/10.3389/fpsyg.2022.897689.
Simon, P. D., & Zeng, L. M. (2024). Behind the scenes of adaptive learning: A scoping review of
teachers’ perspectives on the use of adaptive learning technologies. Education Sciences, 14(12), Article 1413. https://doi.org/10.3390/educsci14121413.
Unwin, T. (2008). Survey of e-learning in Africa based on a questionnaire survey of people on the e-learning Africa database. UNESCO.
Vo, T. K. A. (2025). Transforming language learning with AI: Adaptive systems, assessments and ethical implications (review 2020–2024). MDPI.
Wang, H., Tlili, A., Huang, R., Cai, Z., Li, M., Cheng, Z., Yang, D., Li, M., Zhu, X., & Fei, C. (2023). Examining the applications of intelligent tutoring systems in real educational contexts: A systematic literature review from the social-experiment perspective. Education and Information Technologies. https://doi.org/10.1007/s10639-022-11555-x. PMC
Wilschut, T., Sense, F., & van Rijn, H. (2024). Speaking to remember: Model-based adaptive vocabulary learning using automatic speech recognition. Computer Speech & Language, 84, Article 101578. https://doi.org/10.1016/j.csl.2023.101578.
Yusuf, M. O., & Afolabi, A. O. (2010). Effects of computer-assisted instruction (CAI) on secondary school students’ performance in biology. Turkish Online Journal of Educational Technology, 9(1), 62–69.
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