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Chan, Wendy; Oh, Jimin – Journal of Experimental Education, 2023
Many generalization studies in education are typically based on a sample of 30-70 schools while the inference population is at least twenty times larger. This small sample to population size ratio limits the precision of design-based estimators of the population average treatment effect. Prior work has shown the potential of small area estimation…
Descriptors: Generalization, Computation, Probability, Sample Size
Shah, Mamta; Foster, Aroutis; Talafian, Hamideh; Barany, Amanda; Petrovich, Mark E., Jr. – Journal of Experimental Education, 2021
This research project applied Projective Reflection (PR) as a theoretical and methodological framework to "facilitate" learning as identity exploration. PR was used to iteratively design and implement three versions of "Virtual City Planning," an augmenting virtual learning environment (AVLE) course in a science museum…
Descriptors: High School Students, Identification (Psychology), STEM Education, Self Concept
Reilly, Joseph M.; McGivney, Eileen; Dede, Chris; Grotzer, Tina – Journal of Experimental Education, 2021
Despite increasing calls for science education that utilizes immersive technologies and authentically model scientific inquiry, little is known about how well curricula leveraging these technologies impact students' science identity. This paper presents a mixed-methods study of identity exploration in 7th grade science students using a three-week…
Descriptors: Science Education, Educational Technology, Technology Uses in Education, Grade 7
Glassman, Michael; Kuznetcova, Irina; Lin, Tzu-Jung; Tilak, Shantanu; Wang, Qiannan; Walling, Amanda – Journal of Experimental Education, 2021
This paper discusses the role of Multi-User Virtual Environments (MUVEs) in the development of epistemic learner identity. MUVEs might help educators create the types of tasks and intellectual open spaces helping students with learner identity development in the information age. MUVEs can create new possibilities for dissemination and sharing of…
Descriptors: Virtual Classrooms, Self Concept, Thinking Skills, Critical Thinking
Tapola, Anna; Jaakkola, Tomi; Niemivirta, Markku – Journal of Experimental Education, 2014
This study investigated changes in elementary school students' (n = 140) situational interest as a function of achievement goal orientation profiles and task characteristics. The authors repeatedly measured situational interest during a simulated science learning task in 2 task conditions that differed in the concreteness of the task elements. The…
Descriptors: Elementary School Students, Goal Orientation, Computer Simulation, Science Instruction
Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng – Journal of Experimental Education, 2008
Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…
Descriptors: Sample Size, Computer Simulation, Statistical Analysis, Tests
Fidalgo, Angel M.; Hashimoto, Kanako; Bartram, Dave; Muniz, Jose – Journal of Experimental Education, 2007
In this study, the authors assess several strategies created on the basis of the Mantel-Haenszel (MH) procedure for conducting differential item functioning (DIF) analysis with small samples. One of the analytical strategies is a loss function (LF) that uses empirical Bayes Mantel-Haenszel estimators, whereas the other strategies use the classical…
Descriptors: Bayesian Statistics, Test Bias, Statistical Analysis, Sample Size

Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2002
Used Johnson's transformation (N. Johnson, 1978) with approximate test statistics to test the homogeneity of simple linear regression slopes in the presence of nonnormality and Type I, Type II or complete heteroscedasticity. Computer simulations show that the proposed techniques can control Type I error under various circumstances. (SLD)
Descriptors: Computer Simulation, Error of Measurement, Regression (Statistics)

Gibbons, Jean D.; Chakraborti, S. – Journal of Experimental Education, 1991
A simulation study compared the performance of the Mann-Whitney "U" test, Student's "t" test, and the alternate (separate variance) "t" test for two mutually independent random samples from normal distributions, with both one-tailed and two-tailed alternatives. Type I error probabilities were computed with equal and…
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Mathematical Models

Olejnik, Stephen – Journal of Experimental Education, 1987
This study examined the sampling distribution of the analysis of variance F ratio in the two sample cases when it followed a preliminary test for variance equality. When the population variances were equal, the sampling distribution approximated the theoretical F distribution quite well, but not when population variances differed. (JAZ)
Descriptors: Analysis of Variance, Comparative Analysis, Computer Simulation, Sample Size

Thompson, Bruce – Journal of Experimental Education, 1991
Monte Carlo methods were used to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. For each of 64 research situations, 1,000 random samples were drawn. Both sets of coefficients were roughly equally influenced; some exceptions are noted. (SLD)
Descriptors: Behavioral Science Research, Computer Simulation, Correlation, Matrices

Taylor, Milton – Journal of Experimental Education, 1987
This paper compares the impact of lecture plus a computer simulation and lecture alone on a broad range of measures, such as students' attitudes, attendance, learning, and information seeking behavior. Results showed that in order to maximize the positive effects, the simulation should be implemented as early in the course as possible. (Author/JAZ)
Descriptors: Academic Achievement, Attendance, Computer Simulation, Computer Uses in Education