Balancing AI and Traditional Teaching: Assessing Opportunities and Risk in Education

Abstract

The study focuses on assessing how teachers' and students’ perspectives on the use of AI in education differ. It also aims to find a practical and ethical approach for the strategic balance of traditional teaching and an AI-based approach. The research area is based on the education institutions in Hetauda Sub-metropolitan city. It uses quantitative data collected with a survey questionnaire from 237 participants, 52 teachers, and 185 students. The data are analyzed using both descriptive and inferential statistics with cross-tabulation, threshold analysis, and a risk opportunity matrix. The results from the data analysis showed students strongly preferred the hybrid model, while teachers struggled to balance AI in their traditional approach. The teachers’ confidence and effectiveness closely depend on proper AI training. The findings highlight students’ concerns over AI use. Overall, results suggest that policy guidelines for socio-emotional and ethical balance should be considered before integrating AI in the education system for teachers’ professional development. Based on the results, this study stresses that the success of the hybrid model highly depends on infrastructural robustness and teachers’ preparedness.