Reanalyzing fourth grade math student achievement in Chile: applying hierarchical linear models (HLMS)

Abstract

The purpose of this article is to present the application of Hierarchical Linear Models (HLMs) in reanalyzing fourth grade math student achievement by using 1996 SIMCE data. This article is part of a study that represents a first attempt to explore more sophisticated statistical tech-niques— other than those techniques commonly applied thus far— in order to obtain a better understanding of stu-dent achievement and the effects of schools in Chile. To achieve this goal, two types of school administration are analyzed: municipal and private subsidized schools, respec-tively, utilizing the One-Way ANOVA Model and the Ran-dom-Intercept Model as the primary HLMs. Results indi-cate that there are significant differences not only within, but also between municipal and private subsidized schools in math achievement. However, the significant variation among students and schools remains to be explained.