| Summary: | In modern educational landscapes, the integration of Artificial Intelligence (AI) technologies is swiftly transforming traditional teaching and learning paradigms. AI holds significant promise for personalized learning experiences, increased engagement, and optimized educational outcomes. However, there has been limited attention given to understanding the factors that shape students' intentions to use AI technologies in their learning processes. Addressing this knowledge gap is essential for developing targeted strategies that promote technology acceptance and utilisation among students. This study aims to develop and test a set of instruments to examine the factors influencing students' behavioural intentions to adopt AI technology in educational settings. Building on a comprehensive literature review of AI adoption, this study identifies eight key concepts: Social influence, habit, price value, performance expectancy, facilitating conditions, hedonic motivation, effort expectancy, and behavioural intention. Accordingly, the instruments were designed to measure these concepts. The measurement scales were subsequently evaluated for reliability and validity using data from 50 students who had used AI technologies. Consequently, these instruments can serve as a stepping stone for future research on AI adoption in educational contexts. © 2024 IEEE.
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