Decoding the ChatGPT mystery: A comprehensive exploration of factors driving AI language model adoption

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Abstract
The increasing ubiquity of Artificial Intelligence (AI) chatbots across a variety of sectors has sparked a burgeoning interest in deciphering the determinants that govern their adoption and usage. This study aims to examine the pivotal factors that influence the practical usage of the AI chatbot, ChatGPT, among a sample of university students. Leveraging the theoretical framework of planned behavior, the research model scrutinizes the interplay between knowledge application, perceived intelligence, usability, attitude, subjective norms, perceived behavioral control, trust, behavioral intention, and actual usage. Data procured from a survey of university students were examined through the lens of structural equation modeling. The outcomes reveal that knowledge application, perceived intelligence, and usability have a positive impact on attitudes towards ChatGPT. Perceived intelligence also influences knowledge application, usability, and trust. Concurrently, attitude and subjective norms notably affect behavioral intention. Contrary to expectations, perceived behavioral control did not significantly influence behavioral intention. Trust emerged as a crucial factor steering behavioral intention, which in turn, positively correlates with the actual usage of ChatGPT. These insights enrich the academic discourse on AI chatbot adoption and provide practical implications for AI developers, educators, and policy makers, striving to enhance user engagement with AI systems in educational contexts.

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