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Shunji Wang; Katerina M. Marcoulides; Jiashan Tang; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…
Descriptors: Hypothesis Testing, Error of Measurement, Comparative Analysis, Monte Carlo Methods
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Ilker Cingillioglu; Uri Gal; Artem Prokhorov – Education and Information Technologies, 2024
This study presents a novel approach contributing to our understanding of the design, development, and implementation AI-based systems for conducting double-blind online randomized controlled trials (RCTs) for higher education research. The process of the entire interaction with the participants (n = 1193) and their allocation to test and control…
Descriptors: Artificial Intelligence, Higher Education, Comparative Analysis, College Choice
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Jihoon Kang; Jina Kim – Journal of Baltic Science Education, 2024
While existing studies have underscored the educational benefits of generating explanatory hypotheses (EHs) in response to unexpected outcomes, empirical research on the underlying mechanisms driving their effectiveness in science learning remains limited. Thus, this study aimed to empirically examine the effectiveness of generating an EH for…
Descriptors: Science Instruction, Learning Processes, Protocol Analysis, Scientific Concepts
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Jeffry White – Journal of Educational Research and Practice, 2024
Violations of normality and homogeneity are common in educational data. When this occurs, the use of parametric statistics may be inappropriate. A generalized form of nonparametric analyses based on the Puri and Sen L statistic provides an alternative approach. Using a chi-square distribution, this technique is easy to apply and has significant…
Descriptors: Nonparametric Statistics, Learning Analytics, Evaluation Methods, Guidance