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Jingwen Wang; Xiaohong Yang; Dujuan Liu – International Journal of Web-Based Learning and Teaching Technologies, 2024
The large scale expansion of online courses has led to the crisis of course quality issues. In this study, we first established an evaluation index system for online courses using factor analysis, encompassing three key constructs: course resource construction, course implementation, and teaching effectiveness. Subsequently, we employed factor…
Descriptors: Educational Quality, Online Courses, Course Evaluation, Models
Franz Classe; Christoph Kern – Educational and Psychological Measurement, 2024
We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…
Descriptors: Algorithms, Item Response Theory, Artificial Intelligence, Factor Analysis
Waller, Niels G. – Journal of Educational and Behavioral Statistics, 2023
Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…
Descriptors: Statistics Education, Multivariate Analysis, Factor Analysis, Factor Structure
Garbarino, Jennifer J. – 1996
All parametric analysis focuses on the "synthetic" variables created by applying weights to "observed" variables, but these synthetic variables are called by different names across methods. This paper explains four ways of computing the synthetic scores in factor analysis: (1) regression scores; (2) M. S. Bartlett's algorithm…
Descriptors: Algorithms, Factor Analysis, Regression (Statistics), Scores

Henkel, Thomas George; Wilmoth, James Noel – Journal of Experimental Education, 1992
Principal components extraction with orthogonal and oblique rotations tested the construct validity of the Personal Profile System (PPS) using data from 1,045 senior noncommissioned Air Force officers. Four factors accounted for 85 percent of the total variance, but the results do not completely justify publisher claims for the PPS. (SLD)
Descriptors: Algorithms, Behavior Patterns, Construct Validity, Factor Analysis