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Blanchard, Simon J.; Aloise, Daniel; DeSarbo, Wayne S. – Psychometrika, 2012
The p-median offers an alternative to centroid-based clustering algorithms for identifying unobserved categories. However, existing p-median formulations typically require data aggregation into a single proximity matrix, resulting in masked respondent heterogeneity. A proposed three-way formulation of the p-median problem explicitly considers…
Descriptors: Matrices, Undergraduate Students, Heuristics, Psychology
Ananda B. W. Manage; Stephen M. Scariano – Journal of Statistics Education, 2013
Principal Component Analysis is widely used in applied multivariate data analysis, and this article shows how to motivate student interest in this topic using cricket sports data. Here, principal component analysis is successfully used to rank the cricket batsmen and bowlers who played in the 2012 Indian Premier League (IPL) competition. In…
Descriptors: Factor Analysis, Multivariate Analysis, Data Analysis, Student Interests
Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
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
Brusco, Michael J.; Kohn, Hans-Friedrich; Stahl, Stephanie – Psychometrika, 2008
Dynamic programming methods for matrix permutation problems in combinatorial data analysis can produce globally-optimal solutions for matrices up to size 30x30, but are computationally infeasible for larger matrices because of enormous computer memory requirements. Branch-and-bound methods also guarantee globally-optimal solutions, but computation…
Descriptors: Heuristics, Programming, Data Analysis, Matrices
Wawro, Megan Jean – ProQuest LLC, 2011
In this study, I considered the development of mathematical meaning related to the Invertible Matrix Theorem (IMT) for both a classroom community and an individual student over time. In this particular linear algebra course, the IMT was a core theorem in that it connected many concepts fundamental to linear algebra through the notion of…
Descriptors: Video Technology, Mathematics Education, Group Discussion, Persuasive Discourse
Barker-Plummer, Dave; Cox, Richard; Dale, Robert – International Working Group on Educational Data Mining, 2009
In this paper, we present a study of a large corpus of student logic exercises in which we explore the relationship between two distinct measures of difficulty: the proportion of students whose initial attempt at a given natural language to first-order logic translation is incorrect, and the average number of attempts that are required in order to…
Descriptors: Data Analysis, Logical Thinking, Difficulty Level, Assignments
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
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
Nugent, Rebecca; Ayers, Elizabeth; Dean, Nema – International Working Group on Educational Data Mining, 2009
In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of mastering. As the number of examinees, items, and skills increases, the estimation of even simple cognitive diagnosis models becomes difficult. We adopt a faster, simpler approach:…
Descriptors: Data Analysis, Students, Skills, Cluster Grouping
Boso, Annie – Online Submission, 2011
An action research project was conducted in order to determine effective math fact strategies for first graders. The traditional way of teaching math facts included using timed tests and flashcards, with most students counting on their fingers or a number line. Six new research-based strategies were taught and analyzed to decide which methods…
Descriptors: Focus Groups, Timed Tests, Achievement Tests, Student Journals
Xiang, Yun; Hauser, Carl – Northwest Evaluation Association, 2010
The purpose of this paper is to offer an analytic perspective to policy makers and educational practitioners regarding how to use longitudinal achievement data to evaluate schools. The authors further discuss the potential practical applications of their models for superintendents, researchers, and policy makers. The premise of the study is that…
Descriptors: Academic Achievement, Comparative Analysis, Policy Formation, Data Analysis
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
Bruns, Deborah A.; Cooley, Marissa – Journal of Early Childhood Teacher Education, 2010
Preparing early childhood education (ECE) and early childhood special education (ECSE) professionals to work with young children with and without disabilities entails the acquisition of content, its application, and opportunities for reflection. This article describes a component of an ECSE assessment course focusing on the logistics and process…
Descriptors: Play, Early Childhood Education, Young Children, Evaluation Methods
Savalei, Victoria – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Normal theory maximum likelihood (ML) is by far the most popular estimation and testing method used in structural equation modeling (SEM), and it is the default in most SEM programs. Even though this approach assumes multivariate normality of the data, its use can be justified on the grounds that it is fairly robust to the violations of the…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Maximum Likelihood Statistics

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