ArticleBehavioral sciences (Basel, Switzerland)2024
Pre-Service Teachers' GenAI Anxiety, Technology Self-Efficacy, and TPACK: Their Structural Relations with Behavioral Intention to Design GenAI-Assisted Teaching.
Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Psychological "effects" of digital technology: a meta-analysis.Frontiers in psychology · 2025Pooled it
- Research on the Impact of Generative Artificial Intelligence Usage Behavior on the Learning Outcomes of Higher Vocational 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
- AI self-efficacy and anxiety among university teachers.Scientific reports · 2026Article
- Preschool Teachers' Intentions to Use GenAI: Extending UTAUT.Behavioral sciences (Basel, Switzerland) · 2026Article
- Factors influencing the use of VR technology for safety training among electric industry workers in China: an extended TAM.Scientific reports · 2026Article
- The relationship between teachers' GAI use and students' social-emotional competence: the chain-mediating roles of teachers' AI literacy and AI self-efficacy.BMC psychology · 2026Article
- Multidimensional determinants of generative AI acceptance in foreign language education.Scientific reports · 2026Article
- The predictive effects of AI anxiety on 21st-century skills and lifelong learning tendencies: a study of pre-service teachers in Northern Cyprus.Frontiers in psychology · 2026Article
- Psychological responses and cognitive mechanisms of university teachers in using generative AI in teaching: a configurational path analysis based on the MOA framework.Frontiers in psychology · 2026Article
- Generative AI adoption and its impact on teachers' self-efficacy and instructional confidence in Ghana.Frontiers in artificial intelligence · 2026Article
- What drives preservice teachers' use of generative AI as instructional media? A structural and configurational analysis.Frontiers in artificial intelligence · 2026Article
- Generative AI acceptance and professional autonomy development among Chinese university physical education teachers: a moderated conditional process model.Frontiers in psychology · 2026Article
- Expectancy and value beliefs predicting generative AI use: evidence from Chinese university faculty.Frontiers in psychology · 2026Article
- Sociodemographic factors, anxiety and attitudes toward generative artificial intelligence among nurses.Frontiers in psychiatry · 2026Article
- The impact of AI integration in project preparation in education course on pre-service teachers' innovativeness, AI anxiety, attitudes, and acceptance.BMC psychology · 2025Article
- Exploring Factors Influencing Pre-Service Teachers' Intention to Use GenAI for Instructional Design: A Grounded Theory Study.Behavioral sciences (Basel, Switzerland) · 2025Article
- Adopting Generative AI in Future Classrooms: A Study of Preservice Teachers' Intentions and Influencing Factors.Behavioral sciences (Basel, Switzerland) · 2025Article
- Examining How Preschool Teachers' Positive Psychological Capital Impacts Digital Education Innovation: A Moderated Moderation Analysis of Effort Expectancy and Behavioral Intention.Behavioral sciences (Basel, Switzerland) · 2025Article
- Article
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Authors and funding
5 authors.
Funding
Abstract
Generative artificial intelligence (GenAI) has taken educational settings by storm in the past year due to its transformative ability to impact school education. It is crucial to investigate pre-service teachers' viewpoints to effectively incorporate GenAI tools into their instructional practices. Data gathered from 606 pre-service teachers were analyzed to explore the predictors of behavioral intention to design Gen AI-assisted teaching. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this research integrates multiple variables such as Technological Pedagogical Content Knowledge (TPACK), GenAI anxiety, and technology self-efficacy. Our findings revealed that GenAI anxiety, social influence, and performance expectancy significantly predicted pre-service teachers' behavioral intention to design GenAI-assisted teaching. However, effort expectancy and facilitating conditions were not statistically associated with pre-service teachers' behavioral intentions. These findings offer significant insights into the intricate relationships between predictors that influence pre-service teachers' perspectives and intentions regarding GenAI technology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.