Understanding students’ participation of intelligent teaching: an empirical study considering artificial intelligence usefulness, interactive reward, satisfaction, university support and enjoyment

The new era of technologies represented by artificial intelligence is profoundly reconstructing the field of education. The integration of emerging technologies in intelligent teaching provides new approaches for improving teaching effectiveness and enriching learning experiences. Today, we know little about students' participation in intelligent teaching with the help of artificial intelligence. In this study, we investigated the mechanism of students' involvement in intelligent teaching. We designed a questionnaire for the confirmatory model of the participation of intelligent teaching through literature research and content analysis. After modeling and empirical analysis with the help of partial least structural equation modeling (PLS-SEM) software (SmartPLS 3.0), we found that: satisfaction, university support, perceived enjoyment, and interactive rewards all indirectly affect intelligent teaching participation through mediating variables (i.e., participation intention and interactivity); participation intention and interactivity directly and positively affect intelligent teaching participation; artificial intelligence usefulness positively moderates the relationships between the two mediating variables (participation intention, interactivity) and intelligent teaching participation. Based on the results of the data analysis, this study offered corresponding optimization strategies: improving students' participation experience in intelligent teaching through using the new technology "artificial intelligence"; implementing the teaching philosophy of "teaching for learning, teaching for fun"; applying "student-oriented" approaches to improve the participation intention. The aim is to make education in the future more diverse, equitable, and high-quality.