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Theoretical analysis uncovers generative AI as a dialogic partner in science learning, suggesting new pedagogical chatbot designs and interactional coding methodologies.
This paper presents a theoretical perspective of generative artificial intelligence (AI) as dialogic partner by extending Jonassen’s notion of technology as partner through Bakhtin’s dialogism and insights from science classroom discourse. This reconceptualization shifts AI from a primarily cognitive or informational role towards a dialogic and post-humanist account of human–AI meaning-making, with pedagogical and methodological implications. Pedagogically, the perspective advances more dialogic forms of science learning, as illustrated through the design of a customized chatbot. Methodologically, it opens up a way of analyzing learning with generative AI as an interactional accomplishment, as illustrated through a systematic coding of student–AI chatlogs.
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Kok‐Sing Tang (2026) studied this question.
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