Developing and Testing a Measurement of Behavioral Intention towards Artificial Intelligence in Higher Education: Taking Individual Differences into the Equation

The integration of Artificial Intelligence (AI) into education holds significant potential, yet understanding students' behavioral intentions toward AI, particularly in relation to individual differences, remains under-explored. This study addresses this gap by developing and validating a measurement scale for Chinese university students’ behavioral intentions toward AI, incorporating individual differences through Technology Readiness and Acceptance Model (TRAM). The scale includes four individual factors—optimism, innovativeness, discomfort, and insecurity—alongside traditional TAM constructs such as perceived ease of use, perceived usefulness, and behavioral intention. Data were collected from 401 Chinese university students, and the scale's reliability and validity were tested using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Results indicate that the scale is both reliable and valid, with strong factor loadings and model fit indices. Theoretical and pedagogical implications for higher education are discussed.