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Greenberg, Mark T.; Abenavoli, Rachel – Journal of Research on Educational Effectiveness, 2017
In this article we seek to promote a deeper understanding of the value of universal intervention research in education as well as other fields and to call for greater interdisciplinary learning and discourse. Our goal is to deepen the conversation regarding how to build a stronger research orientation toward longitudinal, population-level outcomes…
Descriptors: Intervention, Educational Research, Research Methodology, Holistic Approach
Rhoads, Christopher – Journal of Educational and Behavioral Statistics, 2017
Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Surveys, Effect Size
Huang, Hung-Yu – Educational and Psychological Measurement, 2017
Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Computation
Joo, Seang-hwane; Wang, Yan; Ferron, John M. – AERA Online Paper Repository, 2017
Multiple-baseline studies provide meta-analysts the opportunity to compute effect sizes based on either within-series comparisons of treatment phase to baseline phase observations, or time specific between-series comparisons of observations from those that have started treatment to observations of those that are still in baseline. The advantage of…
Descriptors: Meta Analysis, Effect Size, Hierarchical Linear Modeling, Computation
Knight, David S.; Landry, Susan; Zucker, Tricia A.; Merz, Emily C.; Guttentag, Cathy L.; Taylor, Heather B. – Journal of Policy Analysis and Management, 2019
We evaluate the cost-effectiveness of two early childhood interventions that use instructional coaching and parent coaching as levers for improvement. The study design allows us to compare the individual effects of each intervention as well as their combined effect on student outcomes. We find that teachers receiving instructional coaching improve…
Descriptors: Cost Effectiveness, Early Childhood Education, Educational Policy, Intervention
Peck, Laura R. – American Journal of Evaluation, 2015
Several analytic strategies exist for opening up the "black box" to reveal more about what drives policy and program impacts. This article focuses on one of these strategies: the Analysis of Symmetrically-Predicted Endogenous Subgroups (ASPES). ASPES uses exogenous baseline data to identify endogenously-defined subgroups, keeping the…
Descriptors: Program Evaluation, Credibility, Prediction, Sample Size
Fugard, Andrew J. B.; Potts, Henry W. W. – International Journal of Social Research Methodology, 2015
Thematic analysis is frequently used to analyse qualitative data in psychology, healthcare, social research and beyond. An important stage in planning a study is determining how large a sample size may be required, however current guidelines for thematic analysis are varied, ranging from around 2 to over 400 and it is unclear how to choose a value…
Descriptors: Sample Size, Research Methodology, Qualitative Research, Computation
Eckerly, Carol; Smith, Russell; Sowles, John – Practical Assessment, Research & Evaluation, 2018
The Discrete Option Multiple Choice (DOMC) item format was introduced by Foster and Miller (2009) with the intent of improving the security of test content. However, by changing the amount and order of the content presented, the test taking experience varies by test taker, thereby introducing potential fairness issues. In this paper we…
Descriptors: Culture Fair Tests, Multiple Choice Tests, Testing, Test Items
Kalkan, Ömür Kaya; Kara, Yusuf; Kelecioglu, Hülya – International Journal of Assessment Tools in Education, 2018
Missing data is a common problem in datasets that are obtained by administration of educational and psychological tests. It is widely known that existence of missing observations in data can lead to serious problems such as biased parameter estimates and inflation of standard errors. Most of the missing data imputation methods are focused on…
Descriptors: Item Response Theory, Statistical Analysis, Data, Test Items
McCoach, D. Betsy; Rifenbark, Graham G.; Newton, Sarah D.; Li, Xiaoran; Kooken, Janice; Yomtov, Dani; Gambino, Anthony J.; Bellara, Aarti – Journal of Educational and Behavioral Statistics, 2018
This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data…
Descriptors: Hierarchical Linear Modeling, Computer Software, Comparative Analysis, Monte Carlo Methods
Zhong, Baichang; Xia, Liying – International Journal of Science and Mathematics Education, 2020
By providing students with a highly interactive and hands-on learning experience, robotics promises to inspire a new generation of mathematical learning. This paper aims to review the empirical evidence on the application of robotics in mathematics education and to define future research perspectives of robot-assisted mathematics education. After…
Descriptors: Robotics, Technology Uses in Education, Mathematics Education, Educational Benefits
McGrath, April – Teaching & Learning Inquiry, 2016
Quantitative results from empirical studies are common in the field of Scholarship of Teaching and Learning (SoTL), but it is important to remain aware of what the results from our studies can, and cannot, tell us. Oftentimes studies conducted to examine teaching and learning are constrained by class size. Small sample sizes negatively influence…
Descriptors: Scholarship, Instruction, Learning, Class Size
Segretin, M. Soledad; Hermida, M. Julia; Prats, Lucía M.; Fracchia, Carolina S.; Ruetti, Eliana; Lipina, Sebastián J. – New Directions for Child and Adolescent Development, 2016
For at least eight decades, researchers have analyzed the association between childhood poverty and cognitive development in different societies worldwide, but few of such studies have been carried out in Latin America. The aim of the present paper is to systematically review the empirical studies that have analyzed the associations between…
Descriptors: Foreign Countries, Children, Poverty, Cognitive Development
Peter, Johannes; Rosman, Tom; Mayer, Anne-Kathrin; Leichner, Nikolas; Krampen, Günter – British Journal of Educational Psychology, 2016
Background: Particularly in higher education, not only a view of science as a means of finding absolute truths (absolutism), but also a view of science as generally tentative (multiplicism) can be unsophisticated and obstructive for learning. Most quantitative epistemic belief inventories neglect this and understand epistemic sophistication as…
Descriptors: Beliefs, Epistemology, Psychology, Factor Analysis
Svetina, Dubravka; Levy, Roy – Journal of Experimental Education, 2016
This study investigated the effect of complex structure on dimensionality assessment in compensatory multidimensional item response models using DETECT- and NOHARM-based methods. The performance was evaluated via the accuracy of identifying the correct number of dimensions and the ability to accurately recover item groupings using a simple…
Descriptors: Item Response Theory, Accuracy, Correlation, Sample Size

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