Teachers’ generative AI self-efficacy, valuing, and integration at work: Examining job resources and demands

Generative AI (genAI) tools have involved rapid and broad uptake since their wide release in late 2022, including among teachers. We investigated several factors that play a role in teachers’ motivation and engagement to harness genAI in teaching and learning. We examined contextual factors (in-school support to apply genAI, time pressure, disruptive student behavior) as predictors of motivation (genAI self-efficacy and genAI valuing) and, in turn, engagement (i.e., genAI integration in teaching-related work and student learning activities) over the course of one school term. Among 368 Australian primary and secondary school teachers, our findings revealed that genAI support was associated with greater genAI self-efficacy and genAI valuing. Time pressure was also linked with greater genAI valuing, whereas disruptive student behavior was not linked with the genAI motivation or engagement variables. In turn, genAI self-efficacy was linked with greater levels of both types of genAI integration. GenAI valuing was associated with greater genAI integration in teaching-related work only. Our results provide knowledge about factors relevant for supporting genAI and its application among teachers in Australia—and also hold relevance to teachers in other countries. • We examined predictors of teachers' motivation to apply generative AI (genAI) at work. • In-school support for genAI predicted greater genAI-related self-efficacy and valuing. • Time pressure at work also predicted greater genAI valuing. • Disruptive student behavior was not linked with genAI self-efficacy and valuing. • GenAI self-efficacy and valuing predicted greater genAI integration at work.