Introduction: The integration of Artificial Intelligence (AI) in education has gained prominence in recent years, promising to revolutionize teaching and learning. However, the effectiveness of AI in education depends on factors such as teachers' adoption of AI technologies, ease of use, and their level of experience with AI tools. Additionally, student interest in learning may moderate the impact of AI on teaching effectiveness. This study explores how these factors—adoption, ease of use, and teacher experience—affect teaching effectiveness and the moderating role of student interest.

Methods: A survey-based quantitative approach was employed, with data collected from 250 teachers and 400 students across various educational institutions. Teachers were surveyed regarding their adoption of AI tools, perceived ease of use, and experience with AI technologies. Students were asked to assess their interest levels in learning through AI-based tools. Teaching effectiveness was measured using a combination of teacher self-assessment and student evaluations.

Results: The findings indicate that adoption and ease of use of AI tools positively correlate with teaching effectiveness. Additionally, teachers with higher experience in using AI report better teaching outcomes. Student interest was found to significantly moderate the relationship between AI adoption and teaching effectiveness, with higher levels of student interest amplifying the positive impact of AI.

Discussion: The study underscores the importance of teacher preparedness and familiarity with AI in enhancing teaching effectiveness. Moreover, the moderating role of student interest highlights the need to align AI-based learning tools with students' preferences to maximize engagement and learning outcomes.

AI Integration in Education, Teaching Effectiveness, Teacher Adoption of AI

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