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Kyle Cox; Ben Kelcey; Hannah Luce – Journal of Experimental Education, 2024
Comprehensive evaluation of treatment effects is aided by considerations for moderated effects. In educational research, the combination of natural hierarchical structures and prevalence of group-administered or shared facilitator treatments often produces three-level partially nested data structures. Literature details planning strategies for a…
Descriptors: Randomized Controlled Trials, Monte Carlo Methods, Hierarchical Linear Modeling, Educational Research
Dong, Yixiao; Dumas, Denis; Clements, Douglas H.; Sarama, Julie – Journal of Experimental Education, 2023
Dynamic Measurement Modeling (DMM) is a recently-developed measurement framework for gauging developing constructs (e.g., learning capacity) that conventional single-timepoint tests cannot assess. The current project developed a person-specific DMM Trajectory Deviance Index (TDI) that captures the aberrance of an individual's growth from the…
Descriptors: Measurement Techniques, Simulation, Student Development, Educational Research
Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Coux, Mickael; Xiao, ZhiMin; Shkedy, Ziv; Kasim, Adetayo – Journal of Experimental Education, 2022
Educational stakeholders are keen to know the magnitude and importance of different interventions. However, the way evidence is communicated to support understanding of the effectiveness of an intervention is controversial. Typically studies in education have used the standardised mean difference as a measure of the impact of interventions. This…
Descriptors: Program Effectiveness, Intervention, Multivariate Analysis, Bayesian Statistics
Shen, Ting; Konstantopoulos, Spyros – Journal of Experimental Education, 2022
Large-scale education data are collected via complex sampling designs that incorporate clustering and unequal probability of selection. Multilevel models are often utilized to account for clustering effects. The probability weighted approach (PWA) has been frequently used to deal with the unequal probability of selection. In this study, we examine…
Descriptors: Data Collection, Educational Research, Hierarchical Linear Modeling, Bayesian Statistics
Aydin, Burak; Algina, James – Journal of Experimental Education, 2022
Decomposing variables into between and within components are often required in multilevel analysis. This method of decomposition should not ignore possible unreliability of an observed group mean (i.e., arithmetic mean) that is due to small cluster sizes and can lead to substantially biased estimates. Adjustment procedures that allow unbiased…
Descriptors: Hierarchical Linear Modeling, Prediction, Research Methodology, Educational Research
Shero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
Chan, Wendy; Hedges, Larry V.; Hedberg, E. C. – Journal of Experimental Education, 2022
Many experimental designs in educational and behavioral research involve at least one level of clustering. Clustering affects the precision of estimators and its impact on statistics in cross-sectional studies is well known. Clustering also occurs in longitudinal designs where students that are initially grouped may be regrouped in the following…
Descriptors: Educational Research, Multivariate Analysis, Longitudinal Studies, Effect Size
Uanhoro, James O.; Wang, Yixi; O'Connell, Ann A. – Journal of Experimental Education, 2021
The standard regression technique for modeling binary response variables in education research is logistic regression. The odds ratios from these models are used to quantify and communicate variable effects. These effects are sometimes pooled together as in a meta-analysis. We argue that this process is problematic as odds ratios calculated from…
Descriptors: Probability, Effect Size, Regression (Statistics), Educational Research
Hartman, Tova; Schachter, Elli – Journal of Experimental Education, 2021
This paper discusses high-school students' perspectives on their participation in educational survey research. Students responded to a Likert-style questionnaire about their school's social-educational portrait and were invited at its end to briefly comment on the survey itself. Qualitative analysis showed that a sizable proportion of students…
Descriptors: Foreign Countries, High School Students, Student Attitudes, Student Participation
Flunger, Barbara; Trautwein, Ulrich; Nagengast, Benjamin; Lüdtke, Oliver; Niggli, Alois; Schnyder, Inge – Journal of Experimental Education, 2021
The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…
Descriptors: Foreign Countries, Middle School Students, Grade 8, Multivariate Analysis
Koopmans, Matthijs – Journal of Experimental Education, 2020
The complex dynamical systems (CDS) approach consists of a family of theories emanating largely from the exact sciences. These theories share a common focus on the behavior of systems and their interrelated parts and are concerned with the processes of stability, change, and unpredictability in those systems. This article takes stock of the…
Descriptors: Educational Change, Systems Approach, Educational Practices, Social Networks
Kaplan, Avi; Garner, Joanna K. – Journal of Experimental Education, 2020
In this commentary, we propose a framework for applying the Complex Dynamical Systems (CDS) approach in educational research. Drawing on the conceptual articles in the special issue for ontological, theoretical, and methodological principles, and on the empirical articles for examples of these principles' application, we suggest six interdependent…
Descriptors: Educational Research, Systems Approach, Theories, Goal Orientation
Jacobson, Michael J. – Journal of Experimental Education, 2020
This article is premised on the observation that in educational research there is an increasing use of terminology and concepts related to the field of complexity and the study of complex physical, biological, and social systems. As we are at an early stage in this cross-fertilization of complex systems ideas and methods in educational research,…
Descriptors: Educational Research, Systems Approach, Research Methodology, Vocabulary
Powell, Marvin G.; Hull, Darrell M.; Beaujean, A. Alexander – Journal of Experimental Education, 2020
Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the…
Descriptors: Probability, Scores, Observation, Educational Research
Xiao, ZhiMin; Higgins, Steve; Kasim, Adetayo – Journal of Experimental Education, 2019
Lord's Paradox occurs when a continuous covariate is statistically controlled for and the relationship between a continuous outcome and group status indicator changes in both magnitude and direction. This phenomenon poses a challenge to the notion of evidence-based policy, where data are supposed to be self-evident. We examined 50 effect size…
Descriptors: Statistical Analysis, Decision Making, Research Methodology, Scores