人工智能与中国MOOC融合背景下用户技术接受度研究— 基于UTAUT模型实证分析

초록

This study conducts an empirical research on user technology acceptance based on prior studies and concepts related to Artificial Intelligence (AI) and MOOCs in China. It further explores the potential impact of regional development levels on users’ technology acceptance by considering the varying levels of development in different regions. The research model is constructed based on the UTAUT theoretical model, with performance expectancy, effort expectancy, social influence, facilitating conditions, and anthropomorphic interaction as independent variables to study their impact on users’ technology usage intentions and attitudes. Additionally, based on the “digital divide” theory, the study treats the location of users as a moderating variable and employs multi-group moderating effect analysis to examine whether the development levels of different regions significantly moderate users’ technology acceptance. SPSS and AMOS software are used to analyze sample data and construct the structural equation model. The results show that the independent variables exhibit a positive relationship with both technology usage intentions and attitudes. However, there is a significant difference in the path relationship of social influence on behavioral intention between developed and underdeveloped regions. Overall, users demonstrate a high level of technology acceptance towards AI MOOCs, whereas in underdeveloped regions, social influence is the only factor that significantly inhibits users’ technology acceptance.

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