Abstract :

Artificial intelligence (AI) is increasingly used in College English teaching through AI tools, online learning platforms, automated feedback, speech practice, and digital learning resources. However, the effectiveness of technology-enhanced teaching depends on how technology is integrated into classroom teaching and whether it promotes students’ learning engagement. When technology use is not closely connected with teaching objectives and appropriate teaching strategies, students’ participation may remain at a surface level. Therefore, this conceptual paper examines how digital technologies, including AI tools, can be integrated with different teaching strategies to support students’ learning engagement in College English classrooms. Based on Learning Engagement Theory, Self-Determination Theory, the Input and Output Hypotheses, and related studies on College English teaching, the paper develops an integrated teaching model that combines interactive teaching, technology-enhanced teaching, and task-based teaching. The model explains how the three teaching strategies can support emotional, cognitive, and behavioral engagement. Interactive teaching can increase students’ interest, enjoyment, and sense of belonging through teacher-student and student-student interaction. Technology-enhanced teaching can provide learning resources, immediate feedback, and support for deep thinking and self-directed learning. Task-based teaching can encourage students to participate in classroom activities, complete meaningful language tasks, and use English for communication. The paper proposes five teaching principles and a five-stage teaching process for College English classrooms in the AI era. It concludes that technology should serve teaching objectives and students’ learning needs. Teachers should combine different teaching strategies, guide students to use AI responsibly, and evaluate both learning processes and learning outcomes.

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Keywords :

artificial intelligence, College English, teaching strategies, interactive teaching, technology-enhanced teaching, task-based teaching, learning engagement

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References :

1. Abraham, M., Arficho, Z., Habtemariam, T., & Demissie, A. (2022). Effects of information communication technology-enhanced teaching training on English language teachers’ pedagogical knowledge and English language proficiency. Cogent Education, 9(1), 2028336. https://doi.org/10.1080/2331186X.2022.2028336
2. Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21, 4. https://doi.org/10.1186/s41239-023-00436-z
3. Cheng, X., & Liu, Y. (2022). Student engagement with teacher written feedback: Insights from low-proficiency and high-proficiency L2 learners. System, 109, 102880. https://doi.org/10.1016/j.system.2022.102880
4. Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2024). Teacher support and student motivation to learn with artificial intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), 3240-3256. https://doi.org/10.1080/10494820.2023.2172044
5. 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. https://doi.org/10.1207/S15327965PLI1104_01
6. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59-109. https://doi.org/10.3102/00346543074001059
7. Godsk, M., & Møller, K. L. (2025). Engaging students in higher education with educational technology. Education and Information Technologies, 30, 2941-2976. https://doi.org/10.1007/s10639-024-12901-x
8. Kok, X. F. K., Pua, C. Y., Puah, S., Devilly, O. Z., Wang, P. C., & Chua, E. C. (2025). The mediating role of student engagement in the relationship between teacher and digital support and learner satisfaction in blended learning environments at higher education. British Educational Research Journal. Advance online publication. https://doi.org/10.1002/berj.4123
9. Krashen, S. D. (1985). The input hypothesis: Issues and implications. Longman.
10. Liu, M., Noordin, N., Ismail, L., & Abdrahim, N. A. (2023). Relationship between student engagement and academic achievement in College English education for non-English majors in China. International Journal of Learning, Teaching and Educational Research, 22(8), 203-232. https://doi.org/10.26803/ijlter.22.8.12
11. Luo, N., Li, H., Zhao, L., Wu, Z., & Zhang, J. (2022). Promoting student engagement in online learning through harmonious classroom environment. The Asia-Pacific Education Researcher, 31(5), 541-551. https://doi.org/10.1007/s40299-021-00606-5
12. Mulyadi, D., Wijayatiningsih, T. D., Singh, C. K. S., & Prastikawati, E. F. (2021). Effects of technology-enhanced task-based language teaching on learners’ listening comprehension and speaking performance. International Journal of Instruction, 14(3), 717-736. https://doi.org/10.29333/iji.2021.14342a
13. Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
14. Swain, M. (1995). Three functions of output in second language learning. In G. Cook & B. Seidlhofer (Eds.), Principle and practice in applied linguistics: Studies in honour of H. G. Widdowson (pp. 125–144). Oxford University Press.
15. Teng, Y., & Wang, X. (2024). Full caption, English proficiency and their relationships with behavioral, cognitive and emotional student engagement in Chinese EFL college content-based instruction video learning. Education and Information Technologies, 29(1), 861-880. https://doi.org/10.1007/s10639-023-12342-y
16. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
17. Walter, Y. (2024). Embracing the future of artificial intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21, 15. https://doi.org/10.1186/s41239-024-00448-3
18. Wong, Z. Y., & Liem, G. A. D. (2022). Student engagement: Current state of the construct, conceptual refinement, and future research directions. Educational Psychology Review, 34(1), 107-138. https://doi.org/10.1007/s10648-021-09628-3
19. Ye, X. (2024). A review of classroom environment on student engagement in English as a foreign language learning. Frontiers in Education, 9, 1415829. https://doi.org/10.3389/feduc.2024.1415829
20. Zhou, S. A., Hiver, P., & Al-Hoorie, A. H. (2023). Dynamic engagement: A longitudinal dual-process, reciprocal-effects model of teacher motivational practice and L2 student engagement. Language Teaching Research. Advance online publication. https://doi.org/10.1177/13621688231158789