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Zendler, Andreas; Klaudt, Dieter; Seitz, Cornelia – Journal of Educational Computing Research, 2014
The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…
Descriptors: Elementary Secondary Education, Computer Science Education, Competence, Cognitive Processes
Shipman, B. A. – PRIMUS, 2012
Through a series of six guided classroom discoveries, students create, via targeted questions, a definition for deciding when two sets have the same cardinality. The program begins by developing basic facts about cardinalities of finite sets. Extending two of these facts to infinite sets yields two statements on comparing infinite cardinalities…
Descriptors: Cognitive Processes, Multidimensional Scaling, Matrices, Questioning Techniques
Dosse, Mohammed Bennani; Berge, Jos M. F. – Psychometrika, 2008
The use of Candecomp to fit scalar products in the context of INDSCAL is based on the assumption that the symmetry of the data matrices involved causes the component matrices to be equal when Candecomp converges. Ten Berge and Kiers gave examples where this assumption is violated for Gramian data matrices. These examples are believed to be local…
Descriptors: Matrices, Equations (Mathematics), Multidimensional Scaling, Comparative Analysis
Peer reviewedCaillez, Francis; Kuntz, Pascale – Psychometrika, 1996
The geometric properties and Euclidean nature of dissimilarity coefficients defined on finite sets are discussed. Several particular transformations are presented that preserve Euclideanarity. The study of a one-parameter family adds to current knowledge of the metric and Euclidean structure of coefficients based on binary data. (SLD)
Descriptors: Equations (Mathematics), Geometry, Matrices, Multidimensional Scaling
Peer reviewedTzeng, Oliver C. S.; May, William H. – Educational and Psychological Measurement, 1979
A strategy for reordering the hierarchical tree structure is presented. While the order of terminal nodes of Johnson's procedure is arbitrary, this procedure will rearrange every triad of nodes under a common least upper node so that the middle node is nonarbitrarily closest to the anchored node. (Author/CTM)
Descriptors: Cluster Analysis, Cluster Grouping, Matrices, Multidimensional Scaling
Peer reviewedHubert, Lawrence J. – Psychometrika, 1979
Based on a simple nonparametric procedure for comparing two proximity matrices (matrices which represent the similarities among a set of objects), a measure of concordance (agreement) is introduced that is appropriate when K independent proximity matrices are available. (Author/JKS)
Descriptors: Matrices, Multidimensional Scaling, Nonparametric Statistics, Technical Reports
Peer reviewedten Berge, Jos M. F. – Psychometrika, 1996
The solution of weakly constrained regression problems typically requires the iterative search, in a given interval, of a point where a certain function has a zero derivative. This note deals with improved bounds for the interval to be searched. (Author)
Descriptors: Estimation (Mathematics), Matrices, Multidimensional Scaling, Regression (Statistics)
Peer reviewedSimmen, Martin W. – Multivariate Behavioral Research, 1996
Several methodological issues in the multidimensional scaling of coarse dissimilarities were studied, examining whether it was better to scale dissimilarity data directly or to scale a new matrix derived from the original by row comparisons. Findings support an alternative row-comparison measure based on the Jacard coefficient. (SLD)
Descriptors: Comparative Analysis, Matrices, Multidimensional Scaling, Research Methodology
Peer reviewedLevin, Joseph; Brown, Morton – Psychometrika, 1979
Two least squares procedures for symmetrization of a conditional proximity matrix are derived. The solutions provide multiplicative constants for scaling the rows or columns of the matrix to maximize symmetry. (Author/JKS)
Descriptors: Matrices, Multidimensional Scaling, Proximity, Symmetry
Peer reviewedten Berge, Jos M. F. – Psychometrika, 1991
A globally optimal solution is presented for a class of functions composed of a linear regression function and a penalty function for the sums of squared regression weights. A completing-the-squares approach is used, rather than calculus, because it yields global minimality easily in two of three cases examined. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Mathematical Models, Matrices
Peer reviewedRodgers, Joseph Lee; Thompson, Tony D. – Applied Psychological Measurement, 1992
A flexible data analysis approach is proposed that combines the psychometric procedures seriation and multidimensional scaling. The method, which is particularly appropriate for analysis of proximities containing temporal information, is illustrated using a matrix of cocitations in publications by 18 presidents of the Psychometric Society.…
Descriptors: Citations (References), Cluster Analysis, Mathematical Models, Matrices
Peer reviewedReynolds, Thomas J.; And Others – Psychometrika, 1987
An algorithm for assessing the correspondence of one or more attribute rating variables to a symmetric matrix of dissimilarities is presented. It is useful as an alternative to fitting property variables into a multidimensional scaling space. The relation between the matrix and the variables is determined by evaluating pairs of pairs relations.…
Descriptors: Mathematical Models, Matrices, Multidimensional Scaling, Predictor Variables
Peer reviewedZielman, Berrie; Heiser, Willem J. – Psychometrika, 1993
An algorithm based on the majorization theory of J. de Leeuw and W. J. Heiser is presented for fitting the slide-vector model. It views the model as a constrained version of the unfolding model. A three-way variant is proposed, and two examples from market structure analysis are presented. (SLD)
Descriptors: Algorithms, Classification, Equations (Mathematics), Estimation (Mathematics)
Peer reviewedWeeks, David G.; Bentler, P.M. – Psychometrika, 1982
Restricted multidimensional scaling models, allowing constraints on parameters, are extended to the case of asymmetric data. Examples of several models are provided, using journal citation data. Possible extensions of the models are considered. (Author/JKS)
Descriptors: Bibliographic Coupling, Data Analysis, Mathematical Models, Matrices
Peer reviewedLevin, Joseph – Educational and Psychological Measurement, 1991
A reanalysis of the intercorrelation matrix from a principal components analysis of the Life Styles Inventory was conducted using a Canadian sample. Using nonmetric multidimensional scaling, analyses show an almost perfect circumplex pattern. Results illustrate the inadequacy of factor analytic procedures for the analysis and representation of a…
Descriptors: Attitude Measures, Correlation, Factor Analysis, Foreign Countries
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