Descriptive Conversations: Unpacking the Educational Implications of Large Language Models through a Foucauldian Lens

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Potential Abstract:
Recent advancements in artificial intelligence have led to the development of large language models (LLMs) that have the capacity to generate human-like text responses. In educational settings, the integration of these technologies has raised questions about their impact on teaching and learning practices. This study employs a Foucauldian perspective to examine the ways in which LLMs influence conversations within educational contexts. Drawing on Foucault’s concept of power and discourse, this research explores how LLMs shape the production of knowledge and the construction of subjectivities in educational interactions.

Through a qualitative analysis of descriptive conversations between teachers and LLMs, this study uncovers the power dynamics at play and the implications for educational practice. By examining the discursive practices that emerge in these interactions, this research sheds light on the ways in which LLMs influence the circulation of knowledge and the exercise of authority in educational settings. Furthermore, this study investigates the role of agency and resistance in conversations with LLMs, highlighting the potential for transformative practices within these interactions.

This research contributes to the ongoing discussions about the integration of AI technologies in education and offers insights into the complexities of using LLMs in pedagogical contexts. By applying a Foucauldian lens to analyze conversations with LLMs, this study provides a nuanced understanding of the power dynamics and discursive practices that shape educational interactions in the digital age.

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