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Xiaowen Wang; Kan Kan Chan; Qianru Li; Shing On Leung – Journal of Educational Computing Research, 2024
The interest in Computational Thinking (CT) development among young learners increases with the number of studies located in literature. In this study, a meta-analysis was conducted to address two main objectives: (a) the effectiveness of empirical interventions on the development of CT in children aged of 3-8 years; and (b) the variables that…
Descriptors: Young Children, Computation, Thinking Skills, Meta Analysis
Lu, Zhuotao; Chiu, Ming M.; Cui, Yunhuo; Mao, Weijie; Lei, Hao – Journal of Educational Computing Research, 2023
This meta-analysis determined game-based learning's (GBL) overall effect on students' computational thinking (CT) and tested for moderators, using 28 effect sizes from 24 studies of 2,134 participants. The random effects model results showed that GBL had a significant positive overall effect on students' CT (g = 0.677, 95% confidence interval…
Descriptors: Game Based Learning, Computation, Thinking Skills, Meta Analysis
Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation
James Soland; Yeow Meng Thum – Annenberg Institute for School Reform at Brown University, 2019
Effect sizes in the Cohen's d family are often used in education to compare estimates across studies, measures, and sample sizes. For example, effect sizes are used to compare gains in achievement students make over time, either in pre- and post-treatment studies or in the absence of intervention, such as when estimating achievement gaps. However,…
Descriptors: Effect Size, Academic Achievement, Achievement Gains, Gender Differences
Pustejovsky, James E. – Grantee Submission, 2018
Methods for meta-analyzing single-case designs (SCDs) are needed to inform evidence-based practice in clinical and school settings and to draw broader and more defensible generalizations in areas where SCDs comprise a large part of the research base. The most widely used outcomes in single-case research are measures of behavior collected using…
Descriptors: Meta Analysis, Case Studies, Evidence Based Practice, Behavioral Science Research
Aragón, Estíbaliz; Serrano, Noemí; Navarro, Jose Ignacio – Electronic Journal of Research in Educational Psychology, 2018
Introduction: Differences in learning mathematics between boys and girls are being controversial according to different studies. However, those divergences are not always supported by empirical studies. One of the specific sources of difficulties on this topic is the fluency calculation learning, where performance differences between boys and…
Descriptors: Elementary School Students, Mathematics Education, Elementary School Mathematics, Mathematics Skills
E. C. Hedberg – Grantee Submission, 2016
Background: There is an increased focus on randomized trials for proximal behavioral outcomes in early childhood research. However, planning sample sizes for such designs requires extant information on the size of effect, variance decomposition, and effectiveness of covariates. Objectives: The purpose of this article is to employ a recent large…
Descriptors: Randomized Controlled Trials, Kindergarten, Children, Longitudinal Studies
Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric – Journal of Experimental Education, 2015
This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…
Descriptors: Effect Size, Measurement Techniques, Statistical Analysis, Research Design