Understanding teachers’ willingness to use artificial intelligence-based teaching analysis system: extending TAM model with teaching efficacy, goal orientation, anxiety, and trust

Abstract

ABSTRACT A growing body of research has documented that artificial intelligence (AI) has the potential to facilitate teaching analysis. However, few studies investigated teachers’ attitudes toward AI-based teaching analysis systems. As a tool for analyzing and evaluating teaching quality, teachers’ willingness to use AI-based teaching analysis systems will undoubtedly affect the application effect of the analysis systems. Considering the evaluative properties and the intelligent nature of the systems, we proposed an integrated model by extending the technology acceptance model with fear of evaluation theory and trust in AI. Meanwhile, teaching efficacy and goal orientation were considered as antecedent variables influencing evaluation anxiety. 330 teachers from China responded to the survey regarding their willingness to use the AI-based teaching analysis system. The results indicated that teachers’ trust in AI-based teaching analysis system positively predicted perceived usefulness and willingness to use the system. Evaluation anxiety negatively affected perceived ease of use and teachers’ willingness to use the system. Teaching efficacy and achievement goal orientations both had influences on evaluation anxiety. Implications for future research were proposed based on the findings.