Artificial Intelligence (AI)-Driven Instruction Effects on Biology Students’ Achievement and Ethical Practices in Lagos Island Public and Private Secondary Schools

Abstract

This study investigated the effects of Artificial Intelligence (AI)–driven instruction on students’ academic achievement and ethical classroom practices in Biology among public and private secondary schools in Lagos Island, Lagos State. The study was motivated by concerns over students’ persistent difficulties in Biology and the increasing need to promote ethical behaviour in technology-supported learning environments. A quasi-experimental pre-test, post-test, nonequivalent control group design was adopted. The population comprised Senior Secondary School II (SS II) Biology students in public and private secondary schools in Lagos Island, while a sample of 120 students was selected through a multistage sampling procedure from four selected schools. Two instruments, namely the Biology Achievement Test (BAT) and the Ethical Classroom Practices Questionnaire (ECPQ), were used for data collection. The instruments were validated by experts, while reliability coefficients of 0.82 and 0.79 were obtained for the BAT and ECPQ respectively. Data were analysed using mean, standard deviation, and independent samples t-test at the 0.05 level of significance. The findings revealed that students exposed to AI-driven instruction achieved significantly higher academic performance than those taught using the conventional teaching method. AI-driven instruction also had a significant positive influence on students’ ethical classroom practices. However, no significant differences were found between public and private school students or between male and female students exposed to AI-driven instruction. The study concluded that AI-driven instruction is an effective pedagogical approach for improving students’ academic achievement and promoting ethical classroom behaviour in Biology. It was recommended that schools, teachers, and educational policymakers should encourage the integration of AI-supported instructional technologies into Biology education.