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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
LI Kunmei, HU Kun
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DOI:10.17265/2161-623X/2025.07.006
Nanfang College Guangzhou, Guangzhou, China
This article systematically integrates the powerful generative features of Generative Artificial Intelligence (GAI) with the synergistic features of multi-modal technology and explores a new pedagogical approach to effective language teaching under the context of a lack of active engagement and motivation, and limited accessibility and dynamism of educational materials in traditional English courses in China’s advanced education. This study proposes a novel language teaching model (a three-tier structure) based on a critical review of the usage of GAI and multi-modality in educational environments. This new language teaching model combines GAI with multi-modal technology and centers around the G-M4 cycle (Generation-Input-Interaction-Output-Monitor/Feedback). This model means empowered generative capabilities, a more dynamic and interactive learning environment, multi-modal and creative output, and effective evaluation and prompt feedback. Furthermore, critical aspects that require attention, such as data privacy and ethical responsibilities, are also illustrated.
Generative Artificial Intelligence, multi-modal technology, English teaching, GAI integration
LI Kunmei, HU Kun. (2025). On the Integration of GAI and Multi-modality in English Teaching: A Study on New Language Teaching Model Construction. US-China Education Review A, July 2025, Vol. 15, No. 7, 526-532.
Du, Y., & Gao, H. (2022). Determinants affecting teachers’ adoption of AI-based applications in EFL context: An analysis of analytic hierarchy process. Education and Information Technologies, 27(7), 9357-9384. Retrieved from https://doi.org/10.1007/s10639-022-11001-y
Huang, F. (2023). Examining foreign language teachers’ information literacy: Do digital nativity, technology training, and fatigue matter? The Asia-Pacific Education Researcher, 33, 901-912. Retrieved from https://doi.org/10.1007/s40299-023-00797-z
Huang, W., Hew, K. F., & Fryer, L. K. (2023). Generative AI and the future of education: Ragnarök or reformation? Educational Technology Research and Development, 71(1), 1-14. Retrieved from https://doi.org/10.1007/s11423-023-10231-2
Jewitt, C. (Ed.). (2009). The Routledge handbook of multimodal analysis. London: Routledge.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F. … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. Retrieved from https://doi.org/10.1016/j.lindif.2023.102274
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(3), 537-550. Retrieved from https://doi.org/10.1177/00336882231162873
Kress, G., & van Leeuwen, T. (2020). Multimodal discourse: The modes and media of contemporary communication (2nd ed.). London: Bloomsbury Academic.
Mayer, R. E. (2020). Multimedia learning (3rd ed.). Cambridge: Cambridge University Press. Retrieved from https://www.cambridge.org/us/univerisitypress/subjects/psychology/educational-psychology/multimedia-learning-3rd-edition
Mills, K. A. (2016). Literacy theories for the digital age: Social, critical, multimodal, spatial, material and sensory lenses. Bristol: Multilingual Matters. Retrieved from https://www.multilingual-matters.com/page/detail/?k=9781783094615
Serafini, F. (2014). Reading the visual: An introduction to teaching multimodal literacy. New York: Teachers College Press. Retrieved from https://www.tcpress.com/reading-the-visual-9780807754719
Wang, Z. J., Liu, X. J., & Su, C. Y. (2025). How humans differ from artificial intelligence: A design thinking-based approach to cultivating empathy in an AI-driven society. Journal of Distance Education, 45(6), 20-34. Retrieved from https://doi.org/10.13541/j.cnki.chinade.2025.06.005
Zhang, Z., & Li, J. (2023). Multimodal input in second language learning: A meta-analysis. Language Learning & Technology, 27(1), 1-24. Retrieved from https://doi.org/10125/73518