Comparative Analysis of Academic Performance among Students with and without Disabilities in Inclusive Secondary Schools in Jos Metropolis, Plateau State, Nigeria

This study investigated the prediction of academic performance among students with and without disabilities in inclusive secondary schools in Jos Metropolis, Plateau State, Nigeria. A quantitative cross-sectional predictive research design was adopted. The study population comprised 1,456 students enrolled in inclusive secondary schools, while a sample of 466 respondents, consisting of 231 students with disabilities and 235 students without disabilities, participated in the study. A multistage sampling procedure involving purposive, stratified random, simple random and total enumeration techniques was employed. Data were collected using a structured questionnaire and students’ academic records. Descriptive statistics, simple linear regression, and independent samples t-test were used for data analysis at the 0.05 level of significance. The findings revealed that learning behaviour significantly predicted students’ academic performance (R = .741, Adjusted R2 = .549, F(1,230) = 2690.38, p < .001), indicating that positive behaviours such as regular attendance, classroom participation, effective study habits, assignment completion, and learning motivation contributed substantially to academic achievement. School factors, including teacher support, availability of learning resources, inclusive instructional practices, and assistive technologies, also significantly predicted academic performance (R = .729, Adjusted R2 = .531, F(1,230) = 2502.87, p < .001). Furthermore, a significant difference was found between the academic performance of students with disabilities (Mean = 17.42, SD = 4.21) and those without disabilities (Mean = 18.31, SD = 4.06), with students without disabilities performing significantly better (t(464) = 4.58, p < .001). The study concludes that both learner-related and school-related factors are significant determinants of academic performance in inclusive secondary schools, while students with disabilities continue to experience comparatively lower academic achievement. It is recommended that schools strengthen learner support systems, improve inclusive instructional practices, expand access to assistive technologies, and adopt data-driven approaches, including machine learning, for the early identification and support of students at risk of poor academic performance.

Keywords: academic performance, inclusive education, students with disabilities, learning behaviour, school factors, predictive analytics, secondary schools, Jos Metropolis, Nigeria.