This study examined the influence of socioeconomic factors on secondary school students’ academic achievement using a multilevel regression framework. Academic achievement among secondary school students has remained a major concern in many developing countries, particularly Nigeria, where disparities in parental income, educational background, and school resources continue to widen achievement gaps. Traditional regression models often ignore the hierarchical structure of educational data, where students are nested within schools. This study employed multilevel regression analysis to account for both student-level and school-level variations in academic performance. A cross-sectional survey design was adopted. Data were collected from 1,200 students drawn from 30 secondary schools through stratified random sampling. Students’ academic achievement was measured using standardized examination scores, while socioeconomic variables included parental income, parental education, occupation, family size, access to learning materials, and school infrastructure indicators. Descriptive statistics, intraclass correlation coefficient (ICC), and two-level hierarchical linear models were employed for analysis. Results showed that parental education, household income, availability of textbooks, internet access, and school infrastructure significantly influenced students’ academic achievement. Approximately 21% of the variation in academic performance occurred between schools, while 79% occurred within schools. The findings emphasize the importance of targeted educational policies aimed at reducing socioeconomic inequalities and improving school learning environments. The study recommends increased government intervention in educational funding, scholarship schemes for low-income families, and improved infrastructure in public secondary schools.
Kayode et al. (Sun,) studied this question.