Unleashing Creative Conversations: Poststructural Perspectives on Large Language Models in Educational Networks

Potential Abstract: This research article examines the intersection of creativity, networks, and large language models within educational contexts from a poststructural lens. In recent years, the emergence of large language models, such as GPT-3 and BERT, has revolutionized natural language processing and generated significant interest in their potential applications across various domains, including education. These models have the ability to generate human-like text and engage in sophisticated conversations, raising questions about their implications for teaching, learning, and educational practices. Drawing on poststructural theories that emphasize the fluidity of language, power dynamics, and the construction of knowledge, this study analyzes how these models influence discourse, curriculum design, and pedagogical approaches within educational networks.

Through a qualitative research methodology that includes interviews with educators, students, and researchers, as well as document analysis of educational texts and online interactions, this study seeks to uncover the ways in which large language models shape creative conversations in educational settings. By exploring the affordances and limitations of these models through a poststructural lens, this research aims to provide insights into the potential disruptions and transformations they bring to traditional educational practices. Ultimately, this study contributes to the ongoing dialogue on the integration of artificial intelligence in education and the implications for equity, agency, and power dynamics within educational networks.

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