An Empirical Study of Undergraduate Satisfaction and Adoption Intentions of Artificial Intelligence in Chengdu, China - Aijia, Jiang (Scholar: Human Sciences, 2025)
Purpose: The research aimed to investigate the important factors impacting the satisfaction and intention to use Artificial Intelligence of Undergraduates in Chengdu, China. The conceptual framework presented cause-and-effect relationships between informational support, emotional support, perceived ease of use, perceived usefulness, satisfaction, attitude, and intention to use. Research design, data, and methodology: At Sichuan University of Media and Communications in Chengdu, China, undergraduate students were given a questionnaire by the researcher using a quantitative approach (n=500). Non-probability sampling included judgmental sampling to select four art majors of Sichuan University of Media and Communications, quota sampling to define the sample size, and convenience sampling to collect data and distribute the questionnaires online and offline. The researcher used structural equation modeling (SEM) and confirmatory factor analysis (CFA) to analyze the data Results: The results show that informational support, emotional support, perceived usefulness, and perceived ease of use have a significant effect on satisfaction, and satisfaction, as an intermediate variable, has a significant effect on the intention to use. Also, the attitude has a significant effect on the intention to use. Conclusions: To enhance the adoption of AI in higher education, it is essential to continuously address factors influencing student satisfaction and intention to use AI. Additionally, ongoing feedback should be provided to refine and adapt the AI implementation.