Enhancing Agricultural Science Student's Performance in School Examinations through Artificial Intelligence Generated Instructions and Pedagogy.

Abstract

This study examined the effectiveness of Artificial Intelligence (AI)–generated instruction and pedagogy in enhancing Agricultural Science students' performance in external examinations such as the West African Examinations Council (WAEC) and the National Examinations Council (NECO). The persistent decline and inconsistent performance of secondary school students in Agricultural Science have been attributed to traditional teaching methods, inadequate instructional materials, and limited use of modern educational technologies. Consequently, the integration of Artificial Intelligence in teaching and learning has emerged as a promising approach for improving instructional delivery and students' academic outcomes. The study adopted a quasi-experimental research design using a pretest–posttest non-equivalent control group design. The population consisted of Senior Secondary School II (SS II) students offering Agricultural Science in public secondary schools. A sample of 100 students was selected using multi-stage sampling techniques and divided into experimental and control groups. The experimental group was taught using AI-generated instructional strategies, while the control group received conventional teaching. Data were collected using the Agricultural Science Achievement Test (ASAT). The instrument was validated by experts in Agricultural Science Education, and Measurement and Evaluation, and its reliability was established using the test–retest method. Data were analyzed using mean, standard deviation, and independent sample t-test at 0.05 level of significance. The findings revealed that students taught using AI-generated instruction performed significantly better than those taught using conventional teaching methods. The results also showed that AI-supported pedagogy improved students' engagement, understanding, and retention of Agricultural Science concepts. The study concluded that integrating Artificial Intelligence–based instructional strategies can significantly enhance students' academic performance in Agricultural Science. It therefore recommended the adoption of AI-supported instructional tools in secondary school teaching.