Developing Time-Indexed Effect Size Metrics for K–12 Reading and Math Educational Evaluation

Primary data sources for developing the national growth references in K–12 reading and math included existing norms from standardized achievement tests such as the Metropolitan Achievement Tests (MAT), the Comprehensive Tests of Basic Skills/Terra Nova (CTBS/TN), and the Stanford Achievement Test Series (SAT). National longitudinal datasets included the elementary school-level dataset (K to 8th grade) Early Childhood Longitudinal Study, Kindergarten Class of 1998–99 (ECLS-K) and the high school-level dataset (8th to 12th grade) National Education Longitudinal Study of 1988 (NELS:88). These national datasets, together with advanced psychometric and statistical tools such as item response theory (IRT), developmental (vertical) scaling, and hierarchal linear modeling (HLM), offer a new way to measure and examine academic growth. In particular, meta-analytic synthesis of existing norms from test publishers and new norms derived from longitudinal datasets can lead to the development of more valid and reliable references for time-indexed effect size metrics. These metrics provide developmentally appropriate evaluations of educational interventions.

Prior evidence from selected experimental research (Project STAR) and quasi-experimental research (Prospects Title I) will be reevaluated using this growth curve analysis framework, and the time-indexed effect size measures will be compared to those traditional effect size measures that have been computed previously. This research contributes to enhancing our capacity to understand or provide a context for interpreting the size of an effect, a step toward bridging the gap between educational research and practice.