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Huibin Zhang; Zuchao Shen; Walter L. Leite – Journal of Experimental Education, 2025
Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…
Descriptors: Sample Size, Multivariate Analysis, Randomized Controlled Trials, Correlation
Bixi Zhang; Wolfgang Wiedermann – Society for Research on Educational Effectiveness, 2022
Background: Studying causal effects is an important aim in education. Causal relationships indicate how well implements (e.g., interventions) work for the target subjects. A good strategy to get the inference in such relationships is to conduct randomized experiments. However, random assignment is limited in education research, even is discouraged…
Descriptors: Statistical Analysis, Causal Models, Algorithms, Simulation
Jing Huang; Yujie Hu – Journal of Geography in Higher Education, 2025
This systematic review examines the empirical research conducted in the past decade to investigate the application of immersive Virtual Reality (IVR) in geography higher education. Our analysis includes 29 empirical studies published across 25 peer-reviewed articles and delves into IVR applications from four key perspectives: the temporal and…
Descriptors: Computer Simulation, Computer Uses in Education, Geography Instruction, College Instruction
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
Taber, Keith S. – Chemistry Education Research and Practice, 2020
This comment discusses some issues about the use and reporting of experimental studies in education, illustrated by a recently published study that claimed (i) that an educational innovation was effective despite outcomes not reaching statistical significance, and (ii) that this refuted the findings of an earlier study. The two key issues raised…
Descriptors: Chemistry, Educational Innovation, Statistical Significance, Statistical Inference
Finch, W. Holmes; Finch, Maria Hernández – Journal of Experimental Education, 2018
Single subject (SS) designs are popular in educational and psychological research. There exist several statistical techniques designed to analyze such data and to address the question of whether an intervention has the desired impact. Recently, researchers have suggested that generalized additive models (GAMs) might be useful for modeling…
Descriptors: Educational Research, Longitudinal Studies, Simulation, Models
Sales, Adam C.; Hansen, Ben B. – Journal of Educational and Behavioral Statistics, 2020
Conventionally, regression discontinuity analysis contrasts a univariate regression's limits as its independent variable, "R," approaches a cut point, "c," from either side. Alternative methods target the average treatment effect in a small region around "c," at the cost of an assumption that treatment assignment,…
Descriptors: Regression (Statistics), Computation, Statistical Inference, Robustness (Statistics)
Research Trends on the Use of Augmented Reality Technology in Teaching English as a Foreign Language
Takkaç Tulgar, Aysegül; Yilmaz, Rabia Meryem; Topu, Fatma Burcu – Participatory Educational Research, 2022
The main aim of this research is to display research trends in studies on augmented reality (AR) in teaching English as a foreign language by using bibliometric mapping and content analysis. For this purpose, 64 studies in total published up to 2019 were accessed for bibliometric analysis. In addition, 49 articles published between 2007 and 2019…
Descriptors: Technology Uses in Education, Computer Simulation, Educational Technology, Second Language Instruction
Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P. – Journal of Research on Educational Effectiveness, 2016
Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…
Descriptors: Educational Research, Generalization, Sampling, Participant Characteristics
Koopmans, Matthijs – Complicity: An International Journal of Complexity and Education, 2015
The detection of complexity in behavioral outcomes often requires an estimation of their variability over a prolonged time spectrum to assess processes of stability and transformation. Conventional scholarship typically relies on time-independent measures, "snapshots", to analyze those outcomes, assuming that group means and their…
Descriptors: Time, Correlation, Observation, Attendance
Bonett, Douglas G. – Journal of Educational and Behavioral Statistics, 2015
Paired-samples designs are used frequently in educational and behavioral research. In applications where the response variable is quantitative, researchers are encouraged to supplement the results of a paired-samples t-test with a confidence interval (CI) for a mean difference or a standardized mean difference. Six CIs for standardized mean…
Descriptors: Educational Research, Sample Size, Statistical Analysis, Effect Size
McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Halabi, Abdel K.; Essop, Ahmed; Carmichael, Teresa; Steyn, Blanche – Africa Education Review, 2014
This paper examines the relationship between the use of online learning resources and academic performance in an Accounting 1 course conducted at a South African Higher Education Institution. The study employed a quantitative analysis over three academic years comparing the collection of end of year marks and the time spent online. The results…
Descriptors: Accounting, Educational Research, Online Courses, Teaching Methods
Phillips, Shane Michael – ProQuest LLC, 2012
Propensity score matching is a relatively new technique used in observational studies to approximate data that have been randomly assigned to treatment. This technique assimilates the values of several covariates into a single propensity score that is used as a matching variable to create similar groups. This dissertation comprises two separate…
Descriptors: Statistical Analysis, Educational Research, Simulation, Observation