THE IMPACT OF AI-EMBEDDED EDUCATION SYSTEMS ON TEACHERS' WORK PERFORMANCE: AN EXTENSION OF THE D&M INFORMATION SYSTEM SUCCESS MODEL
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This study investigates the impact of AI-Embedded Education Systems on the work performance of K-12 teachers in China, as well as the moderating and direct effects of AI anxiety. Using PLS-SEM, the study analysed the responses of 640 valid participants. The results validate the feasibility and effectiveness of adding AI quality as an independent variable to the information system success model. The results show that information quality, system quality, service quality, and AI quality are positively correlated with satisfaction. At the same time, information quality, system quality, and AI quality are positively correlated with usage, but the hypothesis that service quality is positively correlated with usage is rejected. Usage has a significant positive impact on satisfaction. Both usage and satisfaction have a positive impact on work performance. In addition, AI anxiety was found to have a significant negative impact on work performance. However, the results reject the moderating role of AI anxiety. This study integrates information system success theory and attention control theory to innovatively develop a new AI-Embedded information system success model. The model extends the application domain of information system success models, and the research results provide new perspectives for education policymakers, promote the orderly advancement of China's smart education projects, and provide a reference and model for other countries' development in the field of smart education.
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