DESIGNING AI-CT TEACHER: PEDAGOGICAL PRINCIPLES AND ARCHITECTURE OF A CRITICAL THINKING-ORIENTED AI PLATFORM FOR FUTURE ENGLISH TEACHERS
Keywords:
design-based research, generative AI, critical thinking, pre-service English teachers, educational platform, 6C cycleAbstract
Future English teachers use generative AI daily, but they often accept its answers without checking. Most available AI tools are designed for speed rather than reflection. This paper reports the first phase of a design-based research project. The project runs at Samarkand State Institute of Foreign Languages. This phase aimed to design a web platform for structured critical thinking with AI. The platform is called AI-CT TEACHER. Its design rests on a six-stage cycle: Context, Consult, Critique, Check, Challenge and Conclude. The paper first shows how the design principles were derived. Their sources are critical thinking theory and research on AI in education. It then presents the pedagogical structure, the learning modules and the technical architecture of the prototype. The platform connects to the Gemini model through a secure server-side function. Students therefore never handle API keys. The paper does not report learning outcomes, because the pilot stage has not yet started. Instead, it offers a transparent design rationale that other teacher educators can examine and adapt.
References
Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5-8. https://doi.org/10.3102/0013189X032001005
Facione, P. A. (1990). Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction (The Delphi Report). California Academic Press.
Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006
Halpern, D. F. (1998). Teaching critical thinking for transfer across domains: Dispositions, skills, structure training, and metacognitive monitoring. American Psychologist, 53(4), 449-455. https://doi.org/10.1037/0003-066X.53.4.449
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868
Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). ACM. https://doi.org/10.1145/3706598.3713778
McKenney, S., & Reeves, T. C. (2019). Conducting educational design research (2nd ed.). Routledge.
Paul, R., & Elder, L. (2019). The miniature guide to critical thinking: Concepts and tools (8th ed.). Rowman & Littlefield.
Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676-688. https://doi.org/10.1016/j.tics.2016.07.002
Soleyeva, S. S., & Suleymanova, N. M. (2025). Blended learning: Combining traditional and digital methods in ELT. Proceedings of the International Conference and Annual Business Meeting (ICON-ABM 2025), 1(1), 12-21.
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.
UNESCO. (2024). AI competency framework for teachers. UNESCO.
Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5-23. https://doi.org/10.1007/BF02504682
