Breaking Barriers: A Meta-Analysis of Educator Acceptance of AI Technology in Education

Citation

McGehee, N. (2024). Breaking Barriers: A Meta-Analysis of Educator Acceptance of AI Technology in Education. Michigan Virtual. https://michiganvirtual.org/research/publications/breaking-barriers-a-meta-analysis-of-educator-acceptance-of-ai-technology-in-education/

Abstract

The integration of technology into education has faced resistance for over a century, with each new innovation—from calculators to artificial intelligence (AI)—meeting skepticism from educators. This meta-analysis examines the predictors of technology adoption among teachers, extending foundational frameworks like the Technology Acceptance Model (TAM) to include modern AI tools. By analyzing over 60 studies, the research identifies key factors such as self-efficacy, perceived usefulness, technological complexity, and ethical concerns that influence adoption. With a particular focus on AI, the study explores how barriers like cost, time, and required pedagogical shifts amplify resistance, while highlighting the importance of training, institutional support, and transparency in fostering acceptance. These findings aim to equip educators, policymakers, and developers with actionable insights to bridge the gap between innovation and classroom practice, ensuring technology enhances learning while addressing teachers’ concerns.

Authors

  • McGehee, Nikolas

Reference Type

Report

Keywords

  • Artificial Intelligence
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