Artificial Intelligence, Machine Learning, And Adaptive Learning Technologies: Revolutionizing Personalized English Language Instruction In The 21st Century Classroom
DOI:
https://doi.org/10.29284/y813r308Keywords:
Artificial intelligence, machine learning, adaptive learning, personalized learning, English language instruction, writing skills, language education technology.Abstract
This research investigates the integration of Artificial Intelligence (AI), Machine Learning (ML), and Adaptive Learning technologies to personalize English Language Teaching (ELT) for higher secondary students. The primary focus is to understand how these technologies enhance students' writing skills in an Indian classroom context. A quasi-experimental methodology was adopted involving pre- and post-tests with control and experimental groups. Data were analyzed using SPSS, including paired sample T-tests. Results showed that students exposed to AI tools demonstrated significantly greater improvement in their writing performance compared to those under traditional instruction. The study affirms the potential of AI to shape modern ELT practices by offering personalized, data-driven, and dynamic instructional experiences. It concludes with implications for policy, pedagogy, and future research.
References
1. Al-Samarraie, H., Shamsuddin, A., & Alzahrani, A. I. (2020). A review of research trends in using AI-based educational technologies in higher education. Education and Information Technologies, 25(2), 479-504.
2. Bhatt, R. (2020). Digital education in India: Challenges and prospects. Journal of Educational Technology, 16(2), 35–42.
3. Chen, X., Zou, D., & Xie, H. (2020). Personalized learning in the context of artificial intelligence: A review. Interactive Learning Environments, 30(1), 1-17.
4. Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.
5. Ferguson, R., & Buckingham Shum, S. (2012). Learning analytics to identify exploratory dialogue within synchronous text chat. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, 23–33.
6. Garcia, P., Romero, C., Ventura, S., & De Castro, C. (2009). An architecture for making recommendations to courseware users. User Modeling and User-Adapted Interaction, 19(1), 15–41.
7. Griffiths, M., & Surridge, P. (2019). How adaptive learning systems are impacting learner engagement. British Journal of Educational Technology, 50(5), 2438–2452.
8. Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial Intelligence in Education: Promises and Imlications for Teaching and Learning. Boston: Center for Curriculum Redesign.
9. Hwang, G. J., & Chang, H. F. (2021). A formative assessment-based approach to improving students’ learning attitudes and achievements in writing. Educational Technology Research and Development, 69(3), 1605–1623.
10. Kukulska-Hulme, A., Lee, H., & Norris, L. (2021). Mobile-assisted language learning: Teacher and learner perspectives on AI writing support. ReCALL, 33(2), 151–168.
11. Kumar, M., & Rani, P. (2020). Grammar correction using AI tools: A study in Indian higher secondary classrooms. Asian Journal of English Language Teaching, 30(1), 91–107.
12. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.
13. Lu, X., & Ai, H. (2015). Syntactic complexity in college-level English writing: Differences among writers with diverse L1 backgrounds. Journal of Second Language Writing, 29, 16–27.
14. Nassaji, H. (2016). The effectiveness of feedback in second language acquisition. Language Teaching Research, 20(3), 309–331.
15. Nguyen, A., Gardner, L., & Sheridan, D. (2022). Evaluating the impact of adaptive learning on student performance and engagement. Educational Technology & Society, 25(1), 53–66.
16. Oxford University Press. (2021). English Language Learning with AI: A White Paper on Innovation in ELT. Oxford ELT Research Division.
17. Patel, S., & Srinivasan, R. (2021). A comparative study of AI-based writing assistance tools in Indian ESL contexts. International Journal of Educational Research Review, 6(4), 202–218.
18. Rajendran, S. (2021). AI in Indian Classrooms: A Shift in Pedagogical Paradigms. ELT Journal of South Asia, 45(1), 14–25.
19. Reeves, T. C., & Lin, L. (2020). The research we have is not the research we need. Educational Technology Research and Development, 68(4), 1991–2003.
20. Roscoe, R. D., & McNamara, D. S. (2013). Writing pal: Feasibility of an intelligent writing strategy tutor in the high school classroom. Journal of Educational Psychology, 105(4), 1010–1025.
21. Spector, J. M. (2020). Thinking about the future of learning: An AI-enhanced model. Educational Technology Research and Development, 68(3), 1551–1567.
22. Sun, C., & Yang, L. (2020). Impact of automated feedback on EFL student writing development. Language Learning & Technology, 24(3), 1–22.
23. Suwanarak, K. (2021). Learners’ perceptions toward AI-based feedback on writing in English as a Foreign Language. International Journal of Emerging Technologies in Learning (iJET), 16(6), 118–131.
24. Tomlinson, C. A. (2005). The differentiated classroom: Responding to the needs of all learners. ASCD.
25. Tsai, Y. S., Poquet, O., Gašević, D., Dawson, S., & Pardo, A. (2019). Complexity leadership in learning analytics: Drivers, challenges, and opportunities. British Journal of Educational Technology, 50(6), 2839–2854.
26. Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.
27. Wang, Y., & Heffernan, N. (2012). The effect of automated prompts on student revision in an intelligent tutoring system. Computers & Education, 58(4), 1033–1045.
28. Warschauer, M. (2019). Learning in the Cloud: How (and Why) AI and Adaptive Systems Matter for Language Learners. TESOL Quarterly, 53(2), 498–506.
29. White, C. (2017). The use of AI in ESL feedback and assessment: Moving from correction to cognition. Language Assessment Quarterly, 14(3), 239–255.
30. Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100.
31. Yang, C. C., & Chou, H. W. (2018). The effect of digital feedback on student revision and writing quality. Computers in Human Behavior, 84, 83–93.
32. Yilmaz, R. M., & Baydas, O. (2021). Effects of an adaptive intelligent writing environment on motivation and anxiety in ESL writing. British Journal of Educational Technology, 52(2), 710–725.
33. Zhang, Y., & Zou, D. (2021). Applications of AI writing assistants in education: A systematic literature review. Educational Research Review, 34, 100394.
34. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 1–27.
35. Zhu, M., & Li, S. (2020). Exploring the role of adaptive writing feedback on students' lexical diversity. ReCALL, 32(3), 283–299.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
