An Empirical Investigation into The Influence of AI Adoption and Usability Factors on Teaching Effectiveness: Examining Teachers’ Experience with Artificial Intelligence and The Moderating Role of Student Interest
Keywords:
Artificial Intelligence in Education, Teaching Effectiveness, AI AdoptionAbstract
The rapid integration of Artificial Intelligence (AI) in education has significantly transformed pedagogical practices, teaching effectiveness, and classroom engagement dynamics. This study empirically investigates the influence of AI adoption, perceived ease of use, and teachers’ experience with AI on teaching effectiveness, while examining student interest as a moderating variable. Drawing upon technology acceptance theories and AI-in-education frameworks, the study synthesizes prior literature to construct a conceptual model that explains how usability and experiential factors shape instructional outcomes in AI-supported learning environments. The research highlights that AI adoption is not merely a technological decision but a pedagogical transformation influenced by teachers’ cognitive readiness, trust in AI systems, and institutional support mechanisms. Prior studies emphasize that teachers’ acceptance of AI tools is strongly shaped by pedagogical beliefs and perceived trust (Choi, Jang, & Kim, 2023), which further impacts teaching effectiveness in digital classrooms. Additionally, student interest plays a critical role in strengthening or weakening the relationship between AI-enabled teaching practices and learning outcomes. Using a structured analytical approach grounded in prior empirical findings, the study identifies key determinants of successful AI integration in education, including usability perception, experiential familiarity, and engagement-driven learning environments. The findings contribute to the growing body of literature on AI in education by providing a multidimensional understanding of how human and technological factors interact to enhance teaching effectiveness in contemporary educational ecosystems.
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Copyright (c) 2026 Dr. Reza Moradi, Dr. Shirin Khosravi
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