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

Autor: Chun-Mei Chou, Tsu-Chi Shen, Tsu-Chuan Shen, Chien-Hua Shen
Předmět:
Zdroj: Research & Practice in Technology Enhanced Learning; 3/28/2024, Vol. 19, p1-27, 27p
Abstrakt: Applying AI-supported technology improves teachers' digital capabilities and optimises students' independent learning. This study used a questionnaire to construct and verify a teacher's AI-supported teaching application self-efficacy (AISTASE) measurement that examined reliability and validity and explored the relationship between teachers' AIS-TASE and behaviour. The AIS-TASE scale includes five constructs: self-affirmation, passion for teaching, adherence to hard work, negative consciousness, and positive belief. There were 1456 senior and vocational high school teachers from 45 schools. The measurement analysis results indicated that the scale has reliability, validity, and the scale can be used as a measurement for teachers to judge themselves in AI-supported teaching. The result indicated teachers' AIS-TASE and behaviour towards background variables. It is found that when teachers use technology-instruction integration AI experience, teachers' perception of using AI-supported technology in school and having a positive attitude towards AI experience on "self-affirmation," "passion for teaching," and "positive belief". The measurement can reflect teachers' effectiveness evaluations in AIsupported teaching, which has important implications for theoretical research and practical application in emerging technology teaching. This research discusses the practicalities of AI-supported teaching. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index