Toward the goal of more rapid knowledge accumulation via better meta-analyses, this article explores statistical approaches intended to increase the precision and comparability of effect sizes from education research. The featured estimate of the proposed approach is a standardized mean difference effect size whose numerator is a mean difference…

Children develop and learn within dynamic contexts, yet the simplifying assumptions of common statistical methods often relegate such complexity to unexplained error. This chapter discusses ideas from the dynamic systems literature, which focuses on the interplay within and between components of complex systems, such as individuals and their…

This commentary begins by summarizing the five contributions to this special issue and briefly recapping the background to the topic of student learning in higher education. Narrative and systematic reviews are compared, and the relative value of different bibliographic databases in the context of systematic reviews is assessed. The importance of…

Over the last 10 years, numerous authors have proposed effect size estimators for single-case designs. None, however, has been shown to be equivalent to the usual between-groups standardized mean difference statistic, sometimes called d. The present paper remedies that omission. Most effect size estimators for single-case designs use the…

Using effect size results from Erford et al.'s (2011) meta-analysis for treatment of depression in school-age youth, the authors analyzed 6 commonly used instruments for practical and technical strengths and weaknesses. Effect size estimates from these 6 instruments were compared to indicate likely results when used in future depression outcome…

Quantitative meta-analysis is a very useful, yet underutilized, technique for synthesizing research findings in higher education. Meta-analytic inquiry can be more challenging in higher education than in other fields of study as a result of (a) concerns about the use of regression coefficients as a metric for comparing the magnitude of effects…

The purpose of this document is to describe the methods RAND used to analyze achievement for 23 personalized learning (PL) schools for the 2012-13 through 2013-14 academic years. This work was performed at the request of the Bill & Melinda Gates Foundation (BMGF), as part of a multi-year evaluation contract. The 23 schools were selected from a…

Eta squared measures the proportion of the total variance in a dependent variable that is associated with the membership of different groups defined by an independent variable. Partial eta squared is a similar measure in which the effects of other independent variables and interactions are partialled out. The development of these measures is…

This toolkit, developed by Regional Educational Laboratory (REL) Central in collaboration with York Public Schools in Nebraska, provides a process and tools to help teachers use data from their classroom assessments to evaluate promising practices. The toolkit provides teachers with guidance on how to deliberately apply and study one classroom…

Experimental designs that randomly assign entire clusters of individuals (e.g., schools and classrooms) to treatments are frequently advocated as a way of guarding against contamination of the estimated average causal effect of treatment. However, in the absence of contamination, experimental designs that randomly assign intact clusters to…

The study investigates the effect of e-learning, blended learning and classroom learning on students' achievement. Two experimental groups together with a control group from Umm Al-Qura University in Saudi Arabia were identified randomly. To assess students' achievement in the different groups, pre- and post-achievement tests were used. The…

Psychological theories are statements of constraint. The role of hypothesis testing in psychology is to test whether specific theoretical constraints hold in data. Bayesian statistics is well suited to the task of finding supporting evidence for constraint, because it allows for comparing evidence for 2 hypotheses against each another. One issue…

In this article, the authors address the practicalities of how data should be presented, summarized, and interpreted. There are no exact rules; indeed there are valid concerns that exact rules may be inappropriate and too prescriptive. New procedures evolve, and new methods may be needed to deal with new types of data, just as people know that new…

Using the example of responses from civil engineering students at a very highly ranked participating university, this guide demonstrates the importance of comparative data when using student questionnaire data for undergraduate academic program review. It also emphasizes the advantage of using factor structures for better questionnaire-based…

Longitudinal studies are necessary to examine individual change over time, with group status often being an important variable in explaining some individual differences in change. Although sample size planning for longitudinal studies has focused on statistical power, recent calls for effect sizes and their corresponding confidence intervals…