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Ngocvan Bui; Jessica Collier; Yunus Emre Ozturk; Donggil Song – TechTrends: Linking Research and Practice to Improve Learning, 2025
The popularity of generative AI chatbots, such as ChatGPT, has sparked numerous studies investigating their use in educational contexts. However, it is important to note that chatbots are not a new phenomenon; researchers have explored conversational agents across diverse fields for decades. Conversational agents engage users in natural language…
Descriptors: Computer Mediated Communication, Artificial Intelligence, Technology Uses in Education, Technology Integration
van Laar, Saskia; Braeken, Johan – Practical Assessment, Research & Evaluation, 2021
Despite the sensitivity of fit indices to various model and data characteristics in structural equation modeling, these fit indices are used in a rigid binary fashion as a mere rule of thumb threshold value in a search for model adequacy. Here, we address the behavior and interpretation of the popular Comparative Fit Index (CFI) by stressing that…
Descriptors: Goodness of Fit, Structural Equation Models, Sampling, Sample Size
Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
Oshima, T. C.; Wright, Keith; White, Nick – International Journal of Testing, 2015
Raju, van der Linden, and Fleer (1995) introduced a framework for differential functioning of items and tests (DFIT) for unidimensional dichotomous models. Since then, DFIT has been shown to be a quite versatile framework as it can handle polytomous as well as multidimensional models both at the item and test levels. However, DFIT is still limited…
Descriptors: Test Bias, Item Response Theory, Test Items, Simulation
Beasley, T. Mark – Journal of Experimental Education, 2014
Increasing the correlation between the independent variable and the mediator ("a" coefficient) increases the effect size ("ab") for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation caused by…
Descriptors: Statistical Analysis, Effect Size, Nonparametric Statistics, Statistical Inference
Tipton, Elizabeth; Pustejovsky, James E. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
Descriptors: Randomized Controlled Trials, Sample Size, Effect Size, Hypothesis Testing
Ugille, Maaike; Moeyaert, Mariola; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim – Journal of Experimental Education, 2014
A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…
Descriptors: Effect Size, Statistical Bias, Sample Size, Regression (Statistics)
Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas – Educational and Psychological Measurement, 2014
An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…
Descriptors: Sampling, Test Items, Effect Size, Scaling
Shieh, Gwowen; Jan, Show-Li – Journal of Experimental Education, 2013
The authors examined 2 approaches for determining the required sample size of Welch's test for detecting equality of means when the greatest difference between any 2 group means is given. It is shown that the actual power obtained with the sample size of the suggested approach is consistently at least as great as the nominal power. However, the…
Descriptors: Sampling, Statistical Analysis, Computation, Research Methodology
Sciutto, Mark J. – Teaching of Psychology, 2015
In-class research projects are a valuable way of providing research experience for undergraduate students in psychology. This article evaluates the use of online social networks to supplement sample recruitment for in-class research projects. Specifically, this article presents a systematic analysis of seven student research projects that…
Descriptors: Undergraduate Students, Psychology, Student Projects, Student Research
Citkowicz, Martyna; Hedges, Larry V. – Society for Research on Educational Effectiveness, 2013
In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…
Descriptors: Multivariate Analysis, Effect Size, Sampling, Sample Size
Fritz, Matthew S.; Taylor, Aaron B.; MacKinnon, David P. – Multivariate Behavioral Research, 2012
Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special…
Descriptors: Statistical Analysis, Error of Measurement, Statistical Bias, Sampling
Maggin, Daniel M.; O'Keeffe, Breda V.; Johnson, Austin H. – Exceptionality, 2011
The purpose of this review was to examine the methods used to conduct meta-analyses of single-subject research involving students with and at-risk for disabilities. Specifically, the procedures used for preparing, aggregating, analyzing, and evaluating single-subject data across 68 primary syntheses were examined. In addition to these…
Descriptors: Research Design, Disabilities, Meta Analysis, Statistical Analysis
Menil, Violeta C.; Ye, Ruili – MathAMATYC Educator, 2012
This study serves as a teaching aid for teachers of introductory statistics. The aim of this study was limited to determining various sample sizes when estimating population proportion. Tables on sample sizes were generated using a C[superscript ++] program, which depends on population size, degree of precision or error level, and confidence…
Descriptors: Sample Size, Probability, Statistics, Sampling