Framing Innovation in Education through Ill-Structured Problems: A Derridean Perspective on Generative AI

Potential Abstract:
This research article explores the intersection of ill-structured problems, frames, generative AI, and Derridean philosophy in the context of educational innovation. Ill-structured problems, characterized by their complex, ambiguous nature, present unique challenges and opportunities for fostering innovation in educational settings. Drawing on Derrida’s deconstructive approach, which emphasizes the fluidity and multiplicity of meanings, this study investigates how generative artificial intelligence can be leveraged to facilitate creative problem-solving and knowledge construction in education.

By integrating Derridean principles with AI technologies, this research aims to uncover new insights into the potential of generative AI to support innovative teaching and learning practices. The concept of frames, as conceptual structures that shape our understanding of problems and solutions, serves as a theoretical lens through which to examine how AI systems can dynamically adapt and generate novel perspectives on ill-structured problems in education. Through a series of case studies and simulations, this study demonstrates the capacity of AI to generate diverse frames and foster innovation in educational settings.

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