ArticleBehavioral sciences (Basel, Switzerland)2025
Adopting Generative AI in Future Classrooms: A Study of Preservice Teachers' Intentions and Influencing Factors.
Article in Behavioral sciences (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Beyond Ease of Use: Dynamics of Technology Adoption and Cognitive Load in AI-Assisted Programming for Non-Technical Students.Behavioral sciences (Basel, Switzerland) · 2026Article
- The Impact of Unscaffolded GenAI Use on Pre-Service Teachers' AI Readiness, Self-Regulated Learning, Critical Thinking, and Instructional Design Performance: A Quasi-Experimental Study.Behavioral sciences (Basel, Switzerland) · 2026Article
- What drives preservice teachers' use of generative AI as instructional media? A structural and configurational analysis.Frontiers in artificial intelligence · 2026Article
- Artificial intelligence driven transformation of pediatric eye health education based on bibliometric analysis and a cross-sectional survey.Frontiers in public health · 2026Article
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Authors and funding
3 authors.
Funding
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Abstract
This study investigated pre-service teachers' (PTs) intentions to adopt generative AI (GenAI) tools in future classrooms by applying an extended Technology Acceptance Model (TAM). Participants were enrolled in multiple teacher-preparation programs within a single U.S. higher education institution. Through a structured GenAI-integrated activity using Khanmigo, a domain-specific AI platform for K-12 education, PTs explored AI-supported instructional tasks. Post-activity data were analyzed using PLS-SEM. The results showed that perceived usefulness (PU), perceived ease-of-use (PEU), and self-efficacy (SE) significantly predicted behavioral intention (BI) to adopt GenAI, with SE also influencing both PU and PEU. Conversely, personal innovativeness in IT and perceived cyber risk showed insignificant effects on BI or PU. The findings underscored the evolving dynamics of TAM constructs in GenAI contexts and highlighted the need to reconceptualize ease-of-use and risk within AI-mediated environments. Practically, the study emphasized the importance of preparing PTs not only to operate AI tools but also to critically interpret and co-design them. These insights inform both theoretical models and teacher education strategies, supporting the ethical and pedagogically meaningful integration of GenAI in K-12 education. Theoretical and practical implications are discussed.
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