ArticleFrontiers in psychology2026
Teachers' competence, self-efficacy, and their attitudes toward generative AI in education: a correlational study.
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.
- Domain-Differentiated Generative AI Competency Self-Efficacy Among University EFL Teachers: Patterns and Predictors.Behavioral sciences (Basel, Switzerland) · 2026Article
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Authors and funding
3 authors.
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Abstract
Background: The rapid integration of Generative Artificial Intelligence (GenAI) offers new opportunities and challenges for education, with teacher adoption being a key factor for successful implementation. However, the psychological factors influencing teachers' attitudes toward these tools remain poorly understood. This study explores the relationship between K-12 teachers' digital competence, their self-efficacy for AI integration, and their attitudes toward using GenAI in education. Methods: A quantitative, cross-sectional survey design was used. Data were collected from 352 K-12 teachers in a large urban school district in Indonesia through an online questionnaire. The survey assessed four constructs: General Digital Competence (GDC), AI-Specific Competence (AISC), Teacher Self-Efficacy for AI Integration (TSE-AI), and Attitudes Toward Generative AI in Education (ATGAI-E). Data analysis involved Pearson's correlations and hierarchical multiple regression. Results: The analysis showed strong positive correlations among all variables. Attitudes toward GenAI had the strongest correlation with TSE-AI ( Discussion: The findings indicate that while both general and AI-specific skills are important, a teacher's self-efficacy, their confidence in their ability to use GenAI effectively, is the most powerful predictor of their attitude. This suggests that successful GenAI adoption depends more on psychological empowerment than on technical training alone. Professional development programs should therefore focus on building teachers' confidence through hands-on practice, peer modeling, and supportive feedback to encourage positive engagement with the GenAI classroom.
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