Edith M. Y. Ya

DOI: http://doi.org/10.4208/itl.20260104

Innovative Teaching and Learning , Vol. 8 (2026), Iss. 1 : pp. 31–49

Published online:    2026-5

Abstract

This pedagogical case study details the replacement of traditional peer assessment with a custom AI-driven scaffolding process in the required Teaching English to Speakers of Other Languages (TESOL) course, “Research Skills in Language Studies and TESOL.” Using customized chatbots on the Bytewise platform—a university-integrated AI educational tool—this approach aimed to deliver iterative, formative feedback on various research tasks, including topic formulation, literature review, data collection methods, and writing part of a research proposal, to foster deeper critical engagement and self-reflection. This reflection on practice is informed by qualitative data from two student surveys and detailed feedback from four peer observers via the Open Classroom Initiative. Findings reveal that while students overwhelmingly valued the immediate and personalized AI guidance, they also raised valid concerns about feedback consistency from different chatbots. Concurrently, peer observers commended the dynamic learning cycle and the open classroom session’s crucial emphasis on teaching students to critically evaluate AI-generated text, suggesting gamification could further enhance motivation and meta-cognitive skills. This paper concludes by proposing a refined pedagogical model that balances AI automation with essential human guidance, offering practical insights for educators on fostering students’ critical engagement with these powerful new tools.

Keywords

AI-driven feedback, customizable chatbots, formative assessment, TESOL, English-medium instruction

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