Date of Award
Doctor of Education (Ded)
Educational and School Psychology
William F. Barker, Ph.D.
Wendy F. Dover, Ed.D.
Joseph F. Kovaleski, D.Ed.
Edward M. Levinson, Ed.D.
No Child Left Behind (NCLB, 2001) included a broad spectrum of changes to the federal role in public education, including accountability provisions that mandated states to test all students. In an atmosphere of educational reform and federally mandated high-stakes testing, demands have increased for progress monitoring strategies that reliably predict outcomes on statewide assessments. This study investigated the predictive validity of demographic variables and the Measures of Academic Progress (MAP) Reading in relation to student performance on the South Carolina’s Palmetto Assessment of State Standards (PASS) English language arts (ELA) test. Various demographic predictive factors of student performance were analyzed including sex, race/ethnicity, socioeconomic status, special education, and grade. The specific MAP predictive factors included the MAP Reading RIT score as well as the three MAP Goal Performance areas (i.e., Understanding and Using Literary Texts, Understanding and Using Informational Texts, and Building Vocabulary). Archival test data and demographic information were obtained from five elementary and three middle schools located in the target school district. The sample was comprised of 3,861 students in grades 3-8. The data were analyzed using associational measures based on Cross-tabulation, Multi-factorial Analysis of Variance, Pearson correlation, and Multiple Linear Regression leading to the construction of a hypothetical path model. The main conclusions of the statistical analysis were that: (1)There were no relationships of practical significance between the demographic variables and the PASS ELA scores; (2) There were significant correlations between the various MAP scores; and (3) Although the correlations were statistically significant between the MAP scores and the PASS ELA scores, the very small effect sizes implied that the linear relationships have little practical importance. In conclusion, while evidence was provided to indicate that the overall model, including the three MAP scores, was statistically significant, the low effect size was indicative of a model that had limited mathematical ability to accurately predict the PASS ELA scores.
Maziarz, Amy L., "The Exploration of Demographics and Computer Adaptive Testing in Predicting Performance on State-Mandated Reading Assessments" (2010). Theses and Dissertations (All). 37.