Table 4_Psychometric validation of the Chinese generative artificial intelligence acceptance scale among university students.xlsx

This cross-sectional psychometric validation study adapted and evaluated the 20-item generative artificial intelligence acceptance scale for use in China.</p>Methods<p>Following translation, back-translation, expert review, and pilot testing, data were collected from a convenience sample of 604 university students at six institutions in Yunnan, Anhui, and Zhejiang provinces.

Participants were randomly divided into exploratory and confirmatory subsamples of 302 each.</p>Results<p>Corrected item–subscale correlations ranged from 0.555 to 0.774. Exploratory factor analysis and parallel analysis supported four dimensions—performance expectancy, effort expectancy, facilitating conditions, and social influence—and the unrotated four-factor solution explained 52.22% of the total variance. The correlated four-factor CFA model fitted the second subsample well, scaled χ²(164) = 180.41, p = 0.180, robust CFI = 0.993, robust TLI = 0.992, robust RMSEA = 0.020, and SRMR = 0.035, and fitted significantly better than the three-factor alternative, Δχ²(3) = 102.11, p < 0.001.