EFFECT OF ARTIFICIAL INTELLIGENCE ON THE ACADEMIC PERFORMANCE OF COMPUTER SCIENCE STUDENTS IN SENIOR SECONDARY SCHOOLS IN ZARIA LOCAL GOVERNMENT AREA, KADUNA STATE

Abstract

Conventional computer science pedagogy in sub-Saharan secondary education frequently struggles with high student-to-teacher ratios and limited individualized instructional support. This study examined the effects of Artificial Intelligence (AI)-assisted instruction on senior secondary school students' academic performance, conceptual retention, and learning engagement in Computer Science. A non-equivalent control group quasi-experimental design was adopted, utilizing a sample of 98 Senior Secondary II (SS II) students (Experimental Group n = 50; Control Group n = 48) across two purposively selected schools in Zaria, Kaduna State, Nigeria. Data were collected using a validated 30-item Data Processing Achievement Test (DPAT) administered as pre- and post-tests. Independent sample t-tests demonstrated that students exposed to AI-driven adaptive instructional tools achieved significantly higher post-test mean scores in overall performance (t (98) = 6.02, p < 0.05), conceptual retention (t (98) = 5.12, p < 0.05), and assessment outcomes (t (98) = 5.44, p < 0.05) compared to the control group taught via traditional lecture methods. Furthermore, self-reported engagement indicators revealed marked improvements in the intervention group. The findings confirm that integrating conversational AI chatbots and dynamic data visualizations into STEM curricula significantly enhances cognitive outcomes and knowledge retention. Educational administrators should systematically incorporate adaptive AI platforms into secondary computer science instruction.