Hierarchical Linear Modelling of Student and School Effects on Academic Achievement

Abstract

Hierarchical linear modelling (HLM) and data from the New Brunswick School Climate Study were used to examine student background, school context, and school climate effects on Grade 6 student achievement in mathematics, science, reading, and writing. Gender, socioeconomic status (SES), and Native ethnicity were significant predictors of academic achievement. Schools showed the smallest variation in reading, the largest in mathematics. School mean SES was significant in mathematics, reading, and writing achievement, as was disciplinary climate in mathematics, science, and writing. School size and parental involvement significantly affected only the relationship between mathematics achievement and individual SES. La modelisation lineaire hierarchique et les donnees provenant d'une etude portant sur le climat scolaire au Nouveau-Brunswick (New Brunswick School Climate Study) furent utilisees pour analyser les acquis des 6lves, le contexte scolaire et les effets du climat scolaire sur le rendement d'eleves de 6e ann6e en math6matique, en sciences, en lecture et en c Educational Testing Service, 1999) gives new importance to investigating factors that contribute to student learning. Because education systems have a hierarchical structure (students nested within schools), researchers must examine both student and school characteristics (Bryk & Raudenbush, 1992). Student