AI Insight
This study of 352 K-12 teachers in Indonesia found that teachers' attitudes toward using generative AI in classrooms are most strongly predicted by their self-efficacy (confidence in using AI effectively), accounting for 62% of variance in attitudes. While both general digital competence and AI-specific skills showed positive correlations with attitudes, teacher self-efficacy emerged as the dominant factor, followed by AI-specific competence and general digital skills. The research suggests that psychological empowerment through confidence-building is more critical than technical training alone for successful AI adoption in education.
Why it matters
These findings indicate that professional development programs for educational AI integration should prioritize building teacher confidence through hands-on practice and peer support rather than focusing solely on technical skills training. This evidence-based approach could significantly improve the effectiveness of AI implementation strategies in schools worldwide.
Understand the Science
BackgroundThe 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.MethodsA 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.ResultsThe analysis showed strong positive correlations among all variables. Attitudes toward GenAI had the strongest correlation with TSE-AI (r = 0.75, p < 0.001), followed by AISC (r = 0.69, p < 0.001) and GDC (r = 0.58, p < 0.001). The hierarchical regression model explained 62% of the variance in teachers’ attitudes (Adjusted R2 = 0.61). After accounting for demographic factors, TSE-AI was the most significant predictor (β = 0.48, p < 0.001), with AISC (β = 0.25, p < 0.001) and GDC (β = 0.11, p = 0.015) also contributing.DiscussionThe 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.