SMART LEARNING WITH AI: DECISION FACTORS IN GENERATION Z’S ADOPTION OF CHATGPT USING THE UTAUT2 FRAMEWORK

Abstract

Purpose: This study investigates the factors influencing the adoption and usage of ChatGPT among Generation Z students in higher education, utilizing the UTAUT2 framework. It explores how performance expectancy, effort expectancy, social influence, hedonic motivation, facilitating conditions, price value, and habit contribute to students’ behavioral intention and actual use. Need for the study: The rapid integration of AI tools in education necessitates a deeper understanding of their acceptance and sustained usage. While previous research has explored the general adoption of AI in academia, there is limited empirical evidence on how specific constructs, drive ChatGPT adoption among students. This study addresses this gap by analyzing key determinants affecting student engagement. Methodology: The study employs a quantitative research design, utilizing survey data collected from university students in Poland. Structural equation modeling (SEM) was used to test the relationships between key UTAUT2 constructs and ChatGPT adoption. Findings: Results indicate that performance expectancy, hedonic motivation, and habit significantly predict students' intention to use ChatGPT, while effort expectancy, social influence, and facilitating conditions were less influential. The study highlights the critical role of habitual engagement in sustained use and the importance of intrinsic motivation in AI adoption. Practical Implications: The study provides actionable insights for university administrators, educators, and policymakers. Institutions should implement AI literacy programs to promote responsible and effective usage of ChatGPT. Moreover, developing AI-powered educational tools that foster habitual engagement can enhance student learning. Policymakers should establish ethical guidelines to mitigate concerns about academic integrity and critical thinking in AI-supported education.

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