Multilevel Approach to Exploring Predictors of College Readiness in Reading and Mathematics

Abstract

For high school graduates and non-graduates, this paper explored significant student and school level predictors of college readiness in reading and mathematics for 9,952 students from 52 schools in one of the largest school districts in the United States. This study employed a two-level Hierarchical Generalized Linear Model (HGLM) that included student level (level-1) and school level (level-2) predictors in order to predict three categories of college readiness formed in combination with high school graduates and non-graduates. The results presented the list of significant predictors and across-school variances for predicting college readiness in reading and mathematics. The results found several academic, behavioral, and demographic predictors at student and school levels producing significant effects on college readiness in reading and mathematics. The across-school variance components for predicting the probabilities of mastery in college readiness both in reading and mathematics are found significant.