Hierarchical Linear Modeling of Academic Achievement: An Empirical Study of Student, Teacher, and School Factors

Abstract

This study aims to examine student-, teacher-, and school-level factors' effects on mathematics achievement using a hierarchical linear model (HLM). These factors are derived from a combination of manifest and latent variables, which rely on the context of the time and schooling. A standardized survey was administered to a representative sample of 300 female and male students from 10 schools. The survey included demographic data like age, sex, educational level, and socioeconomic status, as well as academic achievement measures. The data were examined using an HLM model to ascertain the relative importance of student level, school, and teacher on students' achievement in mathematics. The outcomes indicated that factors related to students were the most critical, accounting for 68% of the variation in achievement, followed by school factors at 18%, and finally teacher factors at 14%. These results support that individuality in the student is the most important explanation for variability in achievement but indicate the importance of the school setting and that of the teacher as facilitative but comparatively less influential factors.