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Albreiki, Balqis; Habuza, Tetiana; Zaki, Nazar – International Journal of Educational Technology in Higher Education, 2023
Technological advances have significantly affected education, leading to the creation of online learning platforms such as virtual learning environments and massive open online courses. While these platforms offer a variety of features, none of them incorporates a module that accurately predicts students' academic performance and commitment.…
Descriptors: Identification, At Risk Students, Artificial Intelligence, Academic Achievement
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Beavers, Amy S.; Lounsbury, John W.; Richards, Jennifer K.; Huck, Schuyler W.; Skolits, Gary J.; Esquivel, Shelley L. – Practical Assessment, Research & Evaluation, 2013
The uses and methodology of factor analysis are widely debated and discussed, especially the issues of rotational use, methods of confirmatory factor analysis, and adequate sample size. The variety of perspectives and often conflicting opinions can lead to confusion among researchers about best practices for using factor analysis. The focus of the…
Descriptors: Factor Analysis, Educational Research, Best Practices, Sample Size
Stellefson, Michael; Hanik, Bruce – Online Submission, 2008
When conducting an exploratory factor analysis, the decision regarding the number of factors to retain following factor extraction is one that the researcher should consider very carefully, as the decision can have a dramatic effect on results. Although there are numerous strategies that can and should be utilized when making this decision,…
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Evaluation Methods
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Browne, Michael W. – Psychometrika, 1992
Structural models that yield circumplex inequality patterns are reviewed, focusing on a model developed by T. W. Anderson (1960). A modification is proposed to this model to allow for negative correlations. This model may be reparameterized as a factor analysis model with nonlinear constraints on the factor loadings. (SLD)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Graphs
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