Artificial Intelligence in Education: Implications for Teaching Methods, Classroom Interaction, and Instructional Planning

Abstract

The integration of artificial intelligence (AI) into education has accelerated in recent years, transforming pedagogical practices and reshaping the roles of teachers and learners. This study examined the implications of AI adoption for teaching methods, classroom interaction, and instructional planning. A mixed-methods design was employed, involving survey responses from 180 teachers and in-depth interviews with 20 participants across diverse educational institutions. Quantitative findings revealed that AI enhanced lesson preparation, supported differentiated instruction, and improved assessment and curriculum planning. AI tools also increased student engagement and facilitated teacher–student communication, though concerns persisted about reduced face-to-face interaction. Qualitative insights highlighted three key themes: empowerment through personalization, balancing technology with human interaction, and the need for teacher training and institutional support. The results suggest that AI holds significant promise as a partner in education by enabling data-driven decision-making and adaptive teaching strategies. However, effective integration requires professional development, ethical awareness, and policies that preserve the social and relational dimensions of teaching. The study concludes that AI should complement, rather than replace, human educators, ensuring a balance between technological efficiency and human-centered pedagogy.

Keywords: Artificial intelligence, teaching methods, classroom interaction, instructional planning, teacher training, educational technology