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Pere J. Ferrando; Ana Hernández-Dorado; Urbano Lorenzo-Seva – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…
Descriptors: Correlation, Factor Analysis, Models, Goodness of Fit
Mahatanankoon, Pruthikrai; Wolf, James – Information Systems Education Journal, 2021
Learning a computer programming language is typically one of the basic requirements of being an information technology (IT) major. While other studies previously investigate computer programming self-efficacy and grit, their relationships between "shallow" and "deep" learning (Miller et al., 1996) have not been thoroughly…
Descriptors: Cognitive Processes, Learning Strategies, Introductory Courses, Computer Science Education
Jon-Paul Paolino – Teaching Statistics: An International Journal for Teachers, 2024
This article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging…
Descriptors: Statistics Education, Factor Analysis, Teaching Methods, Introductory Courses
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Vispoel, Walter P.; Lee, Hyeryung; Xu, Guanlan; Hong, Hyeri – Journal of Experimental Education, 2023
Although generalizability theory (GT) designs have traditionally been analyzed within an ANOVA framework, identical results can be obtained with structural equation models (SEMs) but extended to represent multiple sources of both systematic and measurement error variance, include estimation methods less likely to produce negative variance…
Descriptors: Generalizability Theory, Structural Equation Models, Programming Languages, Scores
Yusuf, Abdullahi; Noor, Norah Md – Journal of Computer Assisted Learning, 2023
Background: Several attitude scales have been developed to measure students' attitudes toward computer programming, including the prominent one developed by Cetin and Ozden. The development of these scales stemmed from the elusive nature of attitude and the lack of specific constructs to measure attitude. These instruments measure students'…
Descriptors: Programming, Computer Science Education, Attitude Measures, Student Attitudes
Torres Jiménez, Stephanie; Ramírez-Echeverry, Jhon Jairo; Restrepo-Calle, Felipe – Journal of Educational Computing Research, 2024
This article presents the design, construct validation, and reliability of a self-report instrument in Spanish that aims to characterize different types of strategies that students can use to learn computer programming. We provide a comprehensive overview of the identification of learning strategies in the existing literature, the design and…
Descriptors: Test Construction, Construct Validity, Test Reliability, Questionnaires
Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
Endler Marcel Borges – Journal of Chemical Education, 2023
An understanding of statistical concepts is necessary for a chemist with a complete education. Here, statistical tests were taught using the R Commander and the Factoshiny packages. These packages run on R software and have a graphical user interface (GUI), which allows students to do statistical tests quickly and easily. These packages were…
Descriptors: Statistics Education, Programming Languages, Chemistry, Science Instruction
Pere J. Ferrando; David Navarro-González; Fabia Morales-Vives – Educational and Psychological Measurement, 2025
The problem of local item dependencies (LIDs) is very common in personality and attitude measures, particularly in those that measure narrow-bandwidth dimensions. At the structural level, these dependencies can be modeled by using extended factor analytic (FA) solutions that include correlated residuals. However, the effects that LIDs have on the…
Descriptors: Scores, Accuracy, Evaluation Methods, Factor Analysis
Gök, Ahmet; Karamete, Aysen – Journal of Educational Technology and Online Learning, 2023
The purpose of this study was to adapt the computational thinking scale developed by Tsai, Liang and Hsu (2021) into Turkish in order to determine the computational thinking skill levels of secondary school students according to such basic elements defined by Selby and Woollard (2013) as abstraction, decomposition, algorithmic thinking, evaluation…
Descriptors: Foreign Countries, Computation, Thinking Skills, Computer Literacy
Lai, Rina PY; Ellefson, Michelle R. – Journal of Educational Computing Research, 2023
Computational thinking (CT) is an emerging and multifaceted competence important to the computing era. However, despite the growing consensus that CT is a competence domain, its theoretical and empirical account remain scarce in the current literature. To address this issue, rigorous psychometric evaluation procedures were adopted to investigate…
Descriptors: Computation, Thinking Skills, Competence, Psychometrics
Fu, Qian; Zhang, Li-Wen; Hong, Jon-Chao; Dong, Yan – Australasian Journal of Educational Technology, 2021
Learning programming challenges students who encounter difficulties such as resolving syntax and format errors. These challenges require students to invoke resilience to overcome programming problems and keep trying. In response, this study developed the programming resilience scale for university students (PRSUS). The snowball-sampling method was…
Descriptors: Test Construction, Test Validity, Programming, Resilience (Psychology)
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
Filiz Kuskaya Mumcu; Branko Andic; Mirjana Maricic; Mathias Tejera; Zsolt Lavicza – Journal of Educational Technology and Online Learning, 2025
Many education policy strategy documents at the European Union level, as well as national strategies of various countries, recommend including computational thinking as a fundamental skill in curricula. The professional development of teachers should be supported to disseminate computational thinking in K12 education. Teachers' value beliefs about…
Descriptors: Teacher Attitudes, Value Judgment, Beliefs, Computation