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Damio, Siti Maftuhah – Asian Journal of University Education, 2018
The purpose of this article is to describe the analytic process of a method of data collection known as Q Methodology. This method is an alternative method in collecting data especially suited to research on "points of views" (Coogan & Herrington, 2011, p. 24). The analytic process of Q methodology involves factor analysis, a…
Descriptors: Q Methodology, Data Collection, Factor Analysis, Keyboarding (Data Entry)
Leonard, Simon N.; Fitzgerald, Robert N.; Bacon, Matt – Australasian Journal of Educational Technology, 2016
Emerging technologies offer an opportunity for the development, at the institutional level, of quality processes with greater capacity to enhance learning in higher education than available through current quality processes. These systems offer the potential to extend use of learning analytics in institutional-level quality processes in addition…
Descriptors: Foreign Countries, Educational Technology, Technological Advancement, Quality Assurance
Lee, Soon-Mook – International Journal of Testing, 2010
CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…
Descriptors: Factor Structure, Computer Software, Factor Analysis, Research Methodology
Ayers, Elizabeth; Nugent, Rebecca; Dean, Nema – International Working Group on Educational Data Mining, 2009
A fundamental goal of educational research is identifying students' current stage of skill mastery (complete/partial/none). In recent years a number of cognitive diagnosis models have become a popular means of estimating student skill knowledge. However, these models become difficult to estimate as the number of students, items, and skills grows.…
Descriptors: Data Analysis, Skills, Knowledge Level, Students
Cook, Gary; Linquanti, Robert; Chinen, Marjorie; Jung, Hyekyung – Office of Planning, Evaluation and Policy Development, US Department of Education, 2012
The Elementary and Secondary Education Act (ESEA), as amended by the No Child Left Behind Act of 2001 inaugurated important changes in assessment and accountability for English Learner (EL) students. Specifically, Title III of the law required states to develop or adopt English-language proficiency (ELP) standards aligned with language demands of…
Descriptors: Civil Rights, Elementary Secondary Education, Federal Legislation, Civil Rights Legislation
Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah – Educational and Psychological Measurement, 2009
The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…
Descriptors: Correlation, Evaluation Methods, Data Analysis, Matrices

Kiers, Henk A. L.; And Others – Psychometrika, 1990
An algorithm is described for fitting the DEDICOM model (proposed by R. A. Harshman in 1978) for the analysis of asymmetric data matrices. The method modifies a procedure proposed by Y. Takane (1985) to provide guaranteed monotonic convergence. The algorithm is based on a technique known as majorization. (SLD)
Descriptors: Algorithms, Data Analysis, Generalizability Theory, Matrices
Reed, Donald B.; Furman, Gail Chase – 1992
The use of the 2 x 2 matrix in qualitative data analysis and theory generation is discussed, embracing the perspective that the objective of qualitative research in general and the analysis of qualitative data in particular is the development of theory. A 2 x 2 matrix is considered to be a tabular representation of the relationship of two…
Descriptors: Data Analysis, Factor Structure, Mathematical Models, Matrices

Thomas, Neal; Gan, Nianci – Journal of Educational and Behavioral Statistics, 1997
Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…
Descriptors: Data Analysis, Item Response Theory, Matrices, Maximum Likelihood Statistics

Velicer, Wayne F.; McDonald, Roderick P. – Multivariate Behavioral Research, 1991
The general transformation approach to time series analysis is extended to the analysis of multiple unit data by the development of a patterned transformation matrix. The procedure includes alternatives for special cases and requires only minor revisions in existing computer software. (SLD)
Descriptors: Cross Sectional Studies, Data Analysis, Generalizability Theory, Mathematical Models
Vallejo, Guillermo; Livacic-Rojas, Pablo – Multivariate Behavioral Research, 2005
This article compares two methods for analyzing small sets of repeated measures data under normal and non-normal heteroscedastic conditions: a mixed model approach with the Kenward-Roger correction and a multivariate extension of the modified Brown-Forsythe (BF) test. These procedures differ in their assumptions about the covariance structure of…
Descriptors: Computation, Multivariate Analysis, Sample Size, Matrices
Vigneau, Francois; Bors, Douglas A. – Educational and Psychological Measurement, 2005
The problem of dimensionality with respect to Raven's Advanced Progressive Matrices (APM) specifically and, more generally, "g" or fluid intelligence, has been a long-standing issue. The present article reports two studies examining the dimensionality of both the original Set II of the APM (n = 506) and a short form (n = 644), using principal…
Descriptors: Context Effect, Item Response Theory, Intelligence Tests, Test Items
Padilla, Raymond V.; And Others – 1996
Most of the literature on student retention focuses on what students do "wrong" that leads to departure from college, but there is much to be learned from studying student success in higher education. This article presents a study designed to uncover the strategies that successful minority students employ to overcome barriers to academic…
Descriptors: Academic Achievement, Academic Persistence, College Students, Data Analysis
Cooley, William W.; And Others – 1992
A state educational indicator system being developed by the Pennsylvania Educational Policy Studies (PEPS) project at the University of Pittsburgh (Pennsylvania) is described. The extensive database that has been established as part of the PEPS project includes thousands of variables that are descriptive of the 500 Pennsylvania school districts.…
Descriptors: Classification, Data Analysis, Databases, Educational Change