Teachers’ motivation and engagement to harness generative AI for teaching and learning: The role of contextual, occupational, and background factors

Abstract

Since their release in late 2022, generative AI (genAI) tools have led to widespread use, including among teachers. The aim of our study is to examine several factors that may be implicated in teachers' motivation and engagement to harness genAI in teaching and learning. We examined contextual (i.e., autonomy-supportive leadership, autonomy-thwarting leadership), occupational experience (i.e., professional growth striving, change-related stress), and background factors (i.e., gender, age, teaching experience, contract length, class size, school level) as predictors of motivation (i.e., genAI valuing) and, in turn, engagement (i.e., integration in teaching-related work and student learning activities). Among 339 Australian teachers, our findings revealed that perceived autonomy-supportive leadership, professional growth striving, and change-related stress were linked with greater genAI valuing. In turn, genAI valuing was associated with greater genAI integration in both teaching-related work and student learning activities. Perceived autonomy-thwarting leadership was directly linked with greater genAI integration in student learning activities, and professional growth striving was directly associated with greater genAI integration in teaching-related work. Teachers’ gender and school level were also linked with the motivation and engagement factors, and there were several indirect associations as well. Our results pinpoint areas of focus for future research, policy, and practice to support genAI and its application in schools.