Impact of AI-Mediated Adaptive Learning Systems on Second Language Acquisition

Syed Adil, Ramadevi Sakhamuri


In the ever-changing environment of educational technology, the pursuit of more effective teaching methods continues to be of utmost importance. This study examines the relative effectiveness of adaptive learning systems (ALSs) compared with conventional classroom techniques in the context of second language acquisition (SLA). This study compares the efficiency of ALSs and conventional classroom methods in the context of SLA to determine which approach yields more favorable learning outcomes. This study assessed the attitudes and outcomes of students through a survey that compared conventional classroom settings with those incorporating ALSs. The questionnaire collected information about students’ perspectives on each learning approach without divulging specific details about the ALS technology or classroom methods. The findings reveal an unambiguous preference for ALSs among students compared with conventional methods, which is accompanied by heightened levels of motivation in ALS environments. This suggests that ALSs’ personalized learning and motivation strategies exert a significant influence on learners’ engagement and proficiency in acquiring a second language. This research carries particular significance for educators and curriculum developers because it underscores the potential of ALSs to revolutionize the process of acquiring a second language. By offering tailored instruction and fostering greater learner engagement, ALSs can significantly enhance the learning experience. The key contribution of this research is the direct comparison of ALSs with conventional methods in the area of second language instruction. In demonstrating ALSs’ unique ability to increase motivation and engagement through personalized learning, this study enhances our understanding of effective language teaching strategies.


Keywords: adaptive learning systems, artificial intelligence, second language acquisition, personalized learning, educational technology.



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CHENG, Y., XU, B., LIAN, Z., SHI, Z., & SHI, P. (2021). Adaptive learning control of switched strict-feedback nonlinear systems with dead zone using NN and DOB. IEEE Transactions on Neural Networks and Learning Systems, 34(5), 2503-2512.

ENNOUAMANI, S., & MAHANI, Z. (2017). An overview of adaptive e-learning systems. Proceedings of the 8th International Conference on Intelligent Computing and Information Systems, Cairo, 5-7 December 2017, pp. 342-347.

FERNANDEZ, A., & PATEL, R. (2020). Adaptive learning and second language acquisition: A comparative study. Journal of Language Teaching and Research, 11(5), 765-778.

GARCIA, P. (2019). Effectiveness of adaptive learning systems in language education. Language Learning Journal, 47(2), 158-175.

HWANG, G.J., SUNG, H.Y., HUNG, C.M., & HUANG, I. (2013). A learning style perspective to investigate the necessity of developing adaptive learning systems. Journal of Educational Technology & Society, 16(2), 188-197. Retrieved from

KHAN, A. (2018). Traditional methodologies in SLA: A critical review. Journal of Language Teaching, 62(3), 345-360.

LEE, H., KIM, J., & LEE, J. (2021). Adaptive learning systems in education: A review of trends and applications. The Journal of Educational Research, 114(3), 357-374.

LHAFRA, F.Z., & ABDOUN, O. (2023). Integration of evolutionary algorithm in an agent-oriented approach for an adaptive e-learning. International Journal of Electrical & Computer Engineering, 13(2), 1964-1978.

LI, X., XU, H., ZHANG, J., & CHANG, H.H. (2023). Deep reinforcement learning for adaptive learning systems. Journal of Educational and Behavioral Statistics, 48(2), 220-243.

MINN, S. (2022). AI-assisted knowledge assessment techniques for adaptive learning environments. Computers and Education: Artificial Intelligence, 3, 100050.

MORENO, L., & RODRIGUEZ, P. (2022). Adaptive learning systems in language education: A new era of personalization. Innovative Language Learning Technologies, 19(1), 87-104.

OSADCHYI, V., KRASHENINNIK, I., SPIRIN, O., KONIUKHOV, S., & DIUZHIKOVA, T. (2020). Personalised and adaptive ICT-enhanced learning: а brief review of research from 2010 to 2019. CEUR Workshop Proceedings, 2732, 559-571. Retrieved from

PATEL, R., & GOMEZ, E. (2022). Scalability and accessibility in adaptive language learning technology. International Journal of Language Education, 30(1), 89-107.

SMITH, J., & JONES, M. (2020). Evolution of adaptive learning: From rule-based to AI-driven models. Educational Technology Research and Development, 68(4), 2031-2050.

TAYLOR, D.L., YEUNG, M., & BASHET, A.Z. (2021). Personalized and Adaptive Learning. In: RYOO, J., & WINKELMANN, K. (eds.) Innovative Learning Environments in STEM Higher Education. SpringerBriefs in Statistics. Cham: Springer, pp. 17–34.

THOMSON, S., LEE, K., & ANDERSON, M. (2023). AI in adaptive language learning: Personalization and adaptability. Journal of Applied Linguistics and AI, 25(2), 203-222.

VAGALE, V., NIEDRITE, L., & IGNATJEVA, S. (2020). Implementation of Personalized Adaptive E-Learning System. Baltic Journal of Modern Computing, 8(2), 293-310.

VERRELLI, C.M., & TOMEI, P. (2023). Adaptive learning control for nonlinear systems: A single learning estimation scheme is enough. Automatica, 149, 110833.

WAN, H., & YU, S. (2023). A recommendation system based on an adaptive learning cognitive map model and its effects. Interactive Learning Environments, 31(3), 1821-1839.

WANG, S., CHRISTENSEN, C., CUI, W., TONG, R., YARNALL, L., SHEAR, L., & FENG, M. (2023). When adaptive learning is effective learning: comparison of an adaptive learning system to teacher-led instruction. Interactive Learning Environments, 31(2), 793-803.

ZHANG, Y., & LIU, X. (2021). Long-term efficacy of adaptive learning systems in language education. Journal of Educational Technology & Society, 24(3), 456–471.

ZHOU, Q., ZHAO, D., SHUAI, B., LI, Y., WILLIAMS, H., & XU, H. (2021). Knowledge implementation and transfer with an adaptive learning network for real-time power management of the plug-in hybrid vehicle. IEEE Transactions on Neural Networks and Learning Systems, 32(12), 5298–5308.


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