ArticleFrontiers in psychology2026
Expectancy and value beliefs predicting generative AI use: evidence from Chinese university faculty.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Generative AI adoption and its impact on teachers' self-efficacy and instructional confidence in Ghana.Frontiers in artificial intelligence · 2026Article
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3 authors.
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Abstract
Background: Guided by expectancy-value theory, this study investigated how Chinese university teachers' Generative AI (Gen AI)-specific task values (intrinsic, utility, attainment), perceived Gen AI costs, and Gen AI self-efficacy predict their behavioral intention and frequency of Gen AI use. Methods: From two universities in China, 365 faculty members completed an online survey. Results: Structural equation modeling revealed that utility value and self-efficacy positively predicted behavioral intention, while only self-efficacy was a significant predictor of actual usage frequency. Task values and perceived cost, aside from utility value, did not significantly influence outcomes. Conclusion: These findings highlight the central role of self-efficacy and perceived utility in motivating teachers' adoption of Gen AI, offering theoretical insights for expectancy-value research and practical guidance for professional development initiatives aimed at fostering effective integration of AI in higher education.
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