MDOI Convergence Chronicles 110.1049/CON.2026.01020
110.1049/CON.2026.01020
Article

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

Rebecca J. Collie, Andrew J. Martin, Dragan Gašević 2024 Convergence Chronicles

Abstract

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.

Identifier Metadata

Identifier 110.1049/CON.2026.01020
Canonical mdoi:110.1049/CON.2026.01020
Resolver URL https://mdoi.org/110.1049/CON.2026.01020
Resource URL Open resource
Document URL Open document
Content Type Article
Authors Rebecca J. Collie, Andrew J. Martin, Dragan Gašević
Year 2024
Depositor Convergence Chronicles Organisation
Prefix 110.1049
Registered Aug. 11, 2026
Updated Aug. 11, 2026
Status Active
Visibility Public

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mdoi:110.1049/CON.2026.01020

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