A Conceptual Exploration of Generative AI-Induced Cognitive Dissonance and its Emergence in University-Level Academic Writing

• URL: http://arxiv.org/abs/2502.05698v1
• Date: Sat, 08 Feb 2025 21:31:04 GMT
• Title: A Conceptual Exploration of Generative AI-Induced Cognitive Dissonance and its Emergence in University-Level Academic Writing
• Authors: Carl Errol Seran, Myles Joshua Toledo Tan, Hezerul Abdul Karim, Nouar AlDahoul,
• Abstract summary: This work explores how Generative Artificial Intelligence (GenAI) serves as both a trigger and amplifier of cognitive dissonance (CD) We introduce a hypothetical construct of GenAI-induced CD, illustrating the tension between AI-driven efficiency and the principles of originality, effort, and intellectual ownership. We discuss strategies to mitigate this dissonance, including reflective pedagogy, AI literacy programs, transparency in GenAI use, and discipline-specific task redesigns.
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• Abstract: The integration of Generative Artificial Intelligence (GenAI) into university-level academic writing presents both opportunities and challenges, particularly in relation to cognitive dissonance (CD). This work explores how GenAI serves as both a trigger and amplifier of CD, as students navigate ethical concerns, academic integrity, and self-efficacy in their writing practices. By synthesizing empirical evidence and theoretical insights, we introduce a hypothetical construct of GenAI-induced CD, illustrating the psychological tension between AI-driven efficiency and the principles of originality, effort, and intellectual ownership. We further discuss strategies to mitigate this dissonance, including reflective pedagogy, AI literacy programs, transparency in GenAI use, and discipline-specific task redesigns. These approaches reinforce critical engagement with AI, fostering a balanced perspective that integrates technological advancements while safeguarding human creativity and learning. Our findings contribute to ongoing discussions on AI in education, self-regulated learning, and ethical AI use, offering a conceptual framework for institutions to develop guidelines that align AI adoption with academic values.

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