AI-Generated Visual art in English Language Teaching: a Multimodal Approach to Language Learning

Main Article Content

G.M. Prem Kumar
N. Hema

Abstract

The fast advancement of Generative Artificial Intelligence (GenAI) has opened up new ways of combining visual and linguistic modalities for English teaching. The focus of this research is to study how effective the AI-generated visual art can be as a multimodal instructional tool for enhancing English language skills (listening, speaking, reading, and writing) as well as multimodal literacy in secondary students especially. In line with the Multiliteracies Theory, Social Semiotic Theory of Multimodality and Constructivist Learning Theory, a quasi-experimental pre-test–post-test control group design was used by engaging 100 ESL learners at the Chennai university in India. The experimental and control groups comprised of 50 learners each. The learners in the experimental group were taught English through the use of AI-generated visual images for vocabulary acquisition, reading, writing, grammar, creative expression, and multimodal understanding practice, while the control group participants were taught in the traditional way. The research utilized an English language proficiency test, a set of tasks focused on four language skills assessment, multimodal literacy rubric, questionnaire about students’ impressions, and observations for data collection.The quantitative data from this study were analyzed with the help of different statistical techniques, such as descriptive statistics, paired-sample and independent-sample t-tests, gain-score analysis and ANCOVA. The results showed significant differences between the achievement of the experimental and control groups, with the first group performing better, t(98) = 8.60, p< .001, d = 1.72. The differences in multimodal literacy were also significant, t(98) = 7.03, p < .001, d = 1.41. The results of ANCOVA showed that even after controlling for the pre-test results, there was a significant effect of the type of instructions on the achievement of the participants in the post-test, F(1, 97) = 85.18, p < .001, partial η² = .468. The students in the experimental group had positive feelings and perceived improvement in their creativity skills

Article Details

How to Cite
Kumar, G. P., & Hema, N. (2026). AI-Generated Visual art in English Language Teaching: a Multimodal Approach to Language Learning. CINEFORUM, 66(S7), 518–528. Retrieved from https://revistadecineforum.com/index.php/cf/article/view/1772
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Original Articles

References

Deng, L., & Jamaludin, K. A. (2026). Roles of Generative Artificial Intelligence (GenAI) in English as a Foreign Language (EFL) instruction: A systematic literature review. SAGE Open, 16(1). https://doi.org/10.1177/21582440261418315

Kress, G. (2010). Multimodality: A social semiotic approach to contemporary communication. Routledge.

Li, B., Tan, Y. L., Wang, C., & Lowell, V. (2025). Two years of innovation: A systematic review of empirical generative AI research in language learning and teaching. Computers and Education: Artificial Intelligence, 9, 100445. https://doi.org/10.1016/j.caeai.2025.100445

Lee, S., Choe, H., Zou, D., & Jeon, J. (2025). Generative AI (GenAI) in the language classroom: A systematic review. Interactive Learning Environments, 335–359. https://doi.org/10.1080/10494820.2025.2498537

Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO.

New London Group. (1996). A pedagogy of multiliteracies: Designing social futures. Harvard Educational Review, 66(1), 60–93. https://doi.org/10.17763/haer.66.1.17370n67v22j160u

Yi, Y., & Ang, S. (2022). Multimodality in the English language classroom: A systematic review of literature. Linguistics and Education, 69, 101048. https://doi.org/10.1016/j.linged.2022.101048