Discovering Teachers’ AI Application, Innovation, and Students’ Behavioral Attitudes toward AI in Learning in Secondary Schools in Quetta

Abstract

Aim of the Study: The main objective of this study was to assess the level of teachers’ AI application and innovation and students’ attitudes towards AI in government secondary schools of Quetta, and to determine the relationship between them.

Methodology: The study was based on Davis's (1989) Technology Acceptance Model, Liu et al.'s (2024) Teacher Innovation Theory, and Bandura's (1986) Social Cognitive Theory, which provide a theoretical explanation of the relationship between teachers’ AI application and students’ attitudes. This quantitative study adopted a descriptive and correlational methodology. For this purpose, 368 teachers (128 males, 240 females) and 394 students (216 boys, 178 girls) were selected from 112 government schools of Quetta through stratified random sampling.

Findings: The study findings show that the overall mean for teachers’ AI application and innovation was M = 2.44 (SD = 0.507), which fell between “uncertain” and “applicable”. Only 1.1% of teachers demonstrated the ability to develop innovative AI-based teaching models. The overall mean of students’ behavioral attitudes was M = 2.242 (SD = 0.549), with 65.6% agreeing with the behavioral statements; however, students remained relatively cautious about pursuing a career in AI. Furthermore, linear Regression proved that teachers’ AI application and innovation explained 98.5% of the variation in students’ behavioral attitudes (R² = .985, β = .992).

Conclusion: Overall, the study concludes that students’ attitudes towards AI were positive; however, teachers’ practical AI skills were extremely limited. Therefore, the establishment of AI clubs and career guidance programs at the school level, practical training programs for teachers and longitudinal studies are recommended.