Physics teachers’ challenges of integrating Artificial Intelligence technology as predictor of students’ academic performance in secondary schools in Plateau state

Abstract

This study examined Physics teachers’ challenges of integrating Artificial Intelligence (AI) technology as predictor of students’ academic performance in secondary schools in Plateau State, adopting a predictive correlational survey de sign. The population comprised 311 Physics teachers and 22,985 SSIII students, from which 36 teachers and 393 stu dents were sampled through random sampling. Instruments used were the Physics Teachers’ Level of Understanding Artificial Intelligence Questionnaire (PTLUAIQ, r=0.78) and the Physics Students’ Academic Performance Proforma (PSAPP). Data were analyzed using descriptive statistics and inferential statistic (linear and multiple regression). Find ings revealed a high level of challenges (M=3.64) of integrating AI technology among Physics teachers, with inadequate training, poor internet access, and insufficient infrastructure as major barriers. Gender did not significantly predict students’ academic performance, as mean scores were similar for both male (M=56.23) and female (M=56.37) teachers’ students’ academic performance. The study concludes that improving AI literacy, rather than focusing on gender dif ferences, is vital for enhancing student academic achievement. Recommendations include AI-focused teacher training, embedding AI in teacher education programs, equitable gender policies, and strengthening school digital infrastruc ture.