Developing and validating an AI-supported teaching applications’ self-efficacy scale

Abstract

This study was to construct and verify a teacher Artificial Intelligence (AI) supported teaching applications self-efficacy (AIS-TASE) measurement to examine reliability and validity and to explore the relationship between teachers' AIS-TASE and behaviour. There were 1456 high school teachers from 45 schools. The analysis results indicated that the scale has reliability, validity, and model adaptation. The scale can be used as a tool for teachers to judge themselves in AI-supported teaching. The scale for AIS-TASE includes five constructs: self-affirmation, willingness to teach, adherence to hard work, negative consciousness, and positive belief. From the analysis research of background variables, it is found that when teachers use technology-instruction integration AI experience, their perception use AI-supported technology in school and have a positive attitude towards AI experience on "self-affirmation," "teaching intention," and "positive belief." The measurement can reflect teachers' effectiveness evaluation in AI-supported teaching, which has important implications for the theoretical research and practical application in emerging technology teaching. This research discusses the practical in AI-supported teaching.