Recent literature on school improvement indicates that teacher quality has a large impact on student learning (Aaronson, Barrow, & Sander, 2007; Rivkin, Hanushek & Kane, 2005; Hanushek, Kane, O'Brien, & Rivkin, (2005); Nye, Konstantopoulos, Hedges, 2004; Rockoff 2004). The most effective way to create quality teachers is to identify characteristics of teacher quality, measure those characteristics and provide feedback that promotes professional development. Valid and reliable outcomes from instruments that are based on effective teaching standards are needed to provide feedback to teachers. The Student Teacher Assessment Rubric (STAR) is an evaluation tool designed specifically to be used with student teachers. The purpose of this study was to examine the underlying structure of the STAR using confirmatory factor analysis (CFA). The data were divided into two data sets, with one data set used to examine the fit to the 10-factor model and the second data set used to validate the model. Due to high correlation coefficients among the 10 latent variables, the model specification was changed to a one-factor model. The fit statistics from the CFA for the one-factor model suggested an adequate fit but the number of modifications needed to improve the fit suggested some problems. Implications for measuring complex knowledge and skills needed for effective teaching are discussed.