This study aims to explore the factors influencing Norwegian high school teachers’ instructional resistance to artificial intelligence (AI) in terms of age, instructional AI efficacy, and collective AI beliefs among school staff. Grounded in a robust theoretical framework that integrates technology-use models, social cognitive theory, and organizational culture theory, the article presents the multifaceted challenges and opportunities associated with AI integration in educational settings. The study involved examining the perceptions of 223 teachers, using structural equation modelling to investigate the antecedents of instructional AI resistance. The analysis reveals that the most significant relationship exists between instructional AI efficacy and AI resistance, highlighting the crucial role of teacher competence and confidence in technology adoption. By contrast, the link between age and AI resistance is weaker, reflecting age-related nuances in acceptance patterns. Additionally, the pathway between collective AI beliefs and AI resistance shows a low negative correlation, underscoring the importance of fostering positive communal attitudes for reducing resistance. As anticipated, there is a moderate positive correlation between instructional AI efficacy and teachers’ shared AI beliefs, suggesting a synergistic association that enhances community-wide opinion of AI’s possibilities. These findings are discussed, and insights and recommendations for practice and directions for future research are offered.
This study was conducted in accordance with the highest ethical standards to ensure the protection and dignity of all participants involved. Informed consent was obtained from all participants, who were thoroughly briefed on the purpose and procedures of the study. Participants were assured of their right to withdraw from the study at any point without repercussions and were informed that their identities would remain confidential. Anonymity was preserved by detaching any identifying information from the data collected and securely storing responses to prevent unauthorized access.
Primary Language | English |
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Subjects | Educational Technology and Computing |
Journal Section | Research Article |
Authors | |
Publication Date | August 31, 2025 |
Submission Date | March 27, 2025 |
Acceptance Date | August 28, 2025 |
Published in Issue | Year 2025 Volume: 14 Issue: 2 |