Teachers and schools both play important roles in students' education. Yet, the unique contribution of each to students' growth has rarely been explored. In this dissertation, a Bayesian multilevel model was applied in each of Grades 3 to 5, with students' growth estimated across three seasonal (fall, winter, spring) administrations of a mathematics assessment. Variance in students' within-year growth was then partitioned into student-, classroom-, and school-level components. The expected differences in students' growth between classrooms and schools were treated as indicators of the teacher or school "effect" on students' mathematics growth. Results provided evidence that meaningful differences in students' growth lies both between classrooms within schools, and between schools. The distribution of teacher effects between schools was also examined through the lens of access and equity with systematic sorting of teachers to schools leading to disproportional student access to classrooms where the average growth was above the norm. Further, previous research has documented persistent and compounding teacher effects over time. Systematic teacher sorting results in students' having differential probabilities of being enrolled in multiple "high" or "low" growth classrooms in a row. While clear evidence of teacher sorting was found, the demographic composition of schools did not relate to the sorting, contrary to previous research. The persistence of teacher and school effects was also examined from a previously unexplored angle by examining the effect of students' previous teacher(s) on their subsequent rate of within-year growth during the school year. These effects were found to be small and teacher effects overall were found to decay quite rapidly.

The intense focus on standards and accountability is rapidly altering the education environment. Often the gauge for measuring school effectiveness is performance on high- stake state tests. In this retrospective cohort comparison study, I observe the relation between the use of curriculum-based measures (CBMs) for reading and change on a state test for reading after implementation of systematic decision making (SDM). Over a span of three years, two student cohorts in two elementary schools were observed. In each two-year cohort, students began in third and then moved to fourth grade: Cohort One (2009 - 2011) and Cohort Two (2010 - 2012). Both cohorts participated in fall, winter, and spring [F-W-S] benchmark screening for Passage Reading Fluency (PRF) and took a state test. Additionally, during the 2011-2012 academic year, SDM was implemented for Cohort Two using reading CBMs. This study addressed three questions: (a) What is the affect on reading growth (OAKS-Reading) in the context of SDM with CBMs? (b) What is the correlation between [F-W-S] PRF and OAKS Reading? and (c) What is the relation between within-year growth rates for students at risk and not at risk in the context of SDM with CBMs? I used an independent samples t-test to examine the across year change in reading for both cohorts (OAKS-Reading) to determine whether the implementation of SDM resulted in a significant difference between cohorts. For Cohort Two (using a SDM model), I correlated benchmark screening within-year measures (easyCBM) and OAKS Reading. Finally, I calculated growth rates for at-risk and not-at-risk students within a SDM model to examine whether that model demonstrated evidence of accelerated growth in at-risk students relative to their not-at-risk peers. Results did not indicate a strong relation between SDM and the large-scale, outcome assessment (OAKS-Reading). A Pearson product-moment correlation indicated a strong positive correlation between the formative measure PRF and the large-scale, outcome assessment OAKS-Reading. Results showed both risk categories had accelerated growth in reading fluency between fall and winter compared to between winter and spring. Implications for school practice and research are discussed.