Author: Kok-Sing Tang

DOI: 10.62670/2308-7668.2025.53.3.004

Source: Issue: vol. 53 No. 3:13 October 2025

Publisher: PE "Center of Excellence"

Document type: Research article

Abstract

As generative AI (GenAI) tools like ChatGPT become increasingly integrated into educational practice, the need to develop students’ AI literacy is becoming more urgent. This paper explores how educators can foster AI literacy by rethinking the role of large language models (LLMs) as a dialogic partner in co-constructing knowledge. In addition to positioning AI literacy as the educational goal, this paper further introduces dialogic inquiry as a pedagogical approach to achieve AI literacy. Drawing on Bakhtin’s notion of heteroglossia, dialogic inquiry reframes GenAI not as an authoritative information provider but as a dialogic partner that invites reasoning, perspective-taking, argumentation, and creative thinking. To illustrate dialogic inquiry in practice, the paper presents findings from an educational research project focusing on a customized GenAI chatbot called the Dialogic Science Teacher (DST).

Key words: AI literacy, dialogic inquiry, heteroglossia, AI in education, critical thinking

References

1. Cooper, G., Tang, K.S, & Rappa, A. (2024). Generative artificial intelligence as epistemic
authority? Perspectives from higher education. In: Crompton, H. & Burke. D. (Eds) Artificial Intelligence Applications in Higher Education: Theories, Ethics, and Case Studies for Schools. (pp.106–122). Routledge.
2. Tang, K.S. (2025). AI-textuality: Expanding Intertextuality to Theorize Human-AI Interaction with Generative AI, Applied Linguistics. https://doi.org/10.1093/applin/amaf016
3. Bakhtin, M. M. (1981). The dialogic imagination: four essays. University of Texas Press.
4. Kristeva, J. (1980). Desire in language: A semiotic approach to literature and art. Columbia University Press.
5. Wegerif, R. (2011). Towards a dialogic theory of how children learn to think. Thinking Skills and Creativity, 6(3), pp. 179–190. https://doi.org/10.1016/j.tsc.2011.08.002
6. González-Howard, M., & McNeill, K. L. (2020). Acting with epistemic agency: Characterizing student critique during argumentation discussions. Science Education, 104(6), pp. 953–982.
7. Mortimer, E. F., & Scott, P. (2003). Meaning making in secondary science classrooms. Open University Press.
8. Tang, K.S. (2024). Informing research on generative artificial intelligence from a language and literacy perspective: A metasynthesis of studies in science education, Science Education, 108(5), pp. 1329–1355. https://doi.org/10.1002/sce.21875
9. Tang, K.S. & Putra B. (2025). Generative AI as a dialogic partner: Enhancing multiple perspectives, reasoning, and argumentation in science education with customized chatbots. Journal of Science Education & Technology. https://doi.org/10.1007/s10956-025-10240-1