Factors Affecting AI-Based Educational Interactions in Secondary Schools of Tehran
Keywords:
Educational interactions, artificial intelligence, upper secondary schools in TehranAbstract
This study aims to identify the factors influencing AI-based educational interactions in secondary schools of Tehran. This qualitative study collected data through semi-structured interviews with faculty members in Educational Management and Communication Sciences. Participants were selected via snowball sampling, reaching a theoretical saturation with 14 experts. Data analysis was conducted using thematic analysis in MAXQDA 12, and initial validation of codes considered comprehension, alignment, generalizability, and control. The qualitative analysis revealed that AI-based educational interactions are multi-layered, encompassing 8 main dimensions and 19 components across 91 indicators. These dimensions include teacher–student interactions, student–student interactions, school–parent interactions, AI infrastructure and platform, quality of intelligent educational content, educational data analytics, teacher support, and continuous evaluation and improvement. Results indicate that AI, as a supportive tool, enhances educational interactions through personalized learning paths, real-time feedback, monitoring progress patterns, suggesting activities, and generating analytical reports, thereby improving teacher and school administrator decision-making. Successful AI-based educational interactions depend on implementing an integrated system combining human interactions, infrastructure, data, content, professional teacher support, and continuous evaluation. This model can serve as a practical roadmap for policymakers, school administrators, designers of intelligent systems, and teachers to enhance the quality of AI-supported teaching and learning.
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Copyright (c) 2025 Mansoureh Rahimi, Reza Sourani Yancheshmeh, Babak Nasiri gharghani (Author)
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