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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
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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
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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
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
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Sankaran, Siva; Sankaran, Kris; Bui, Tung – Decision Sciences Journal of Innovative Education, 2023
Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators…
Descriptors: Data Analysis, Programming Languages, Student Attitudes, Computer Science Education
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Chen, Kuanchin; Rea, Alan – Journal of Information Systems Education, 2018
Agile methods and approaches such as eXtreme programming (XP) have become the norm for successful organizations not only in the software industry but also for businesses seeking to improve internal software processes. Pair programming in some form is touted as a major functionality and productivity improvement. However, numerous studies show that…
Descriptors: Computer Software, Programming, Coding, Information Systems
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Kay, Robin H. – Journal of Research on Computing in Education, 1993
Describes a study of 647 preservice teachers in Ontario that used the Computer Ability Survey (CAS) to assess 4 components of computer literacy: software ability, awareness, programming skill, and perceived control. Correlations and validity for the CAS are discussed, and results of a principal-components factor analysis are reported. (Contains 39…
Descriptors: Ability Identification, Computer Literacy, Computer Software, Correlation
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection