Exploring teachers' behavioural intentions to design artificial intelligence-assisted learning in Chinese K-12 education

• Published in: Technology, pedagogy and education Vol. 33; no. 5; pp. 629 - 645
• Main Authors: Wang, Kai, Chai, Ching-Sing, Liang, Jyh-Chong, Sang, Guoyuan
• Format: Journal Article
• Language: English
• Published: Abingdon Routledge 19.10.2024; Taylor & Francis Ltd
• Subjects: Artificial intelligence; behavioural intentions; Influence of Technology; Intention; K-12; Learning; Literacy; Pedagogical Content Knowledge; Professional Autonomy; School Support; technostress; TPACK; China
• ISSN: 1475-939X; 1747-5139
• DOI: 10.1080/1475939X.2024.2369241

As artificial intelligence (AI) advances rapidly, it has been incorporated into formal education to facilitate subject-based learning. Integration of AI technologies to support learning requires teachers to intentionally design AI-assisted learning. However, there have been a limited number of empirical studies investigating teachers' behavioural intentions to design AI-assisted learning. To explore the predictors of teachers' behavioural intentions to design AI-assisted learning and examine the structural relationships among these factors, the authors constructed a structural model of AI literacy, Technological Pedagogical Content Knowledge (TPACK), technostress, school support, teacher agency, teacher autonomy and behavioural intentions. Data from 312 K-12 in-service teachers in China were analysed. The results suggest that TPACK, school support, teacher agency and teacher autonomy positively predict teachers' behavioural intentions to design AI-assisted learning. However, AI literacy and technostress were not statistically associated with teachers' behavioural intentions. On the other hand, TPACK significantly mediated AI literacy and teachers' behavioural intentions.