Multilevel Analysis of School, Teacher, and Student Factors Predicting Science Achievement in Nigerian Public Secondary Schools

This study conducted a multilevel analysis of school-level, teacher-level, and student-level factors predicting science achievement in Nigerian public secondary schools, using nationally distributed data across all six geopolitical zones. Most existing studies employ single-level analytical approaches that fail to disentangle school and classroom effects from individual student characteristics. A multilevel cross-sectional design was used. A nationally stratified sample of 4,800 SS2 students, 480 Science teachers, and 120 secondary schools participated across Lagos, Kano, Enugu, Kaduna, Rivers, and Borno States. Hierarchical Linear Modelling with three levels was used to decompose variance and estimate fixed and random effects. At the student level, science self-efficacy and parental education were strongest predictors. At the teacher level, teaching experience and laboratory instruction quality showed significant effects. At the school level, laboratory adequacy and principal instructional leadership predicted achievement independently. Approximately 28 percent of variance in science achievement was attributable to school-level factors and 20 percent to teacher-level factors. The study makes an original methodological contribution to Nigerian science education by establishing nationally representative multilevel evidence for achievement determinants. Policy recommendations include school-level accountability frameworks and differentiated teacher development by school context. Keywords: multilevel analysis, science achievement, Nigerian secondary schools, hierarchical linear modelling, national study.