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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
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 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 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
Gabriel, Roy M. – 1975
Multidimensional scaling (MDS) a highly reliable measurement technique, often requires an overwhelming task of the subject in the data collection procedure. This investigation was designed to determine the loss of precision in solution associated with five degrees of systematic reduction in the data collection task. Data were simulated via Monte…
Descriptors: Data Analysis, Data Collection, 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 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 reviewedNoma, Elliot; Smith, D. Randall – Multivariate Behavioral Research, 1985
Correspondence analysis can provide spatial or clustering representations by assigning spatial coordinates minimizing the distance between individuals linked by a sociometric relationship. These scales may then be used to identify individuals' locations in a multidimensional representation of a group's structure or to reorder the rows and columns…
Descriptors: Cluster Analysis, Goodness of Fit, Matrices, Multidimensional Scaling
De Ayala, R. J.; Hertzog, Melody A. – 1989
This study was undertaken to compare non-metric multidimensional scaling (MDS) and factor analysis (FA) as means of assessing dimensionality in relation to item response theory (IRT). FA assesses correlation matrices, while MDS performs an analysis of proximity measures. Seven data sets were generated; each differed from the others with respect to…
Descriptors: Comparative Analysis, Error of Measurement, Factor Analysis, Latent Trait Theory
PDF pending restorationRudnitsky, Alan N. – 1977
Three approaches to the graphic representation of similarity and dissimilarity matrices are compared and contrasted. Specifically, Kruskal's multidimensional scaling, Johnson's hierarchical clustering, and Waern's graphing techniques are employed to depict, in two dimensions, data representing the structure of a set of botanical concepts. Each of…
Descriptors: Botany, Cluster Analysis, Cluster Grouping, Comparative Analysis
Peer reviewedMcGrath, William E.; And Others – Library and Information Science Research, 1988
Four models for conceptualizing a circulation matrix containing the number of books borrowed according to subject and majors of student borrowers compare (1) majors; (2) subjects; (3) disciplines, suppressing the distinction between majors and subjects; and (4) majors with subjects. Results of multidimensional scaling analysis of the models are…
Descriptors: Academic Libraries, Higher Education, Library Circulation, Library Collections
Reynolds, Thomas J. – 1976
A method of factor extraction specific to a binary matrix, illustrated here as a person-by-item response matrix, is presented. The extraction procedure, termed ERGO, differs from the more commonly implemented dimensionalizing techniques, factor analysis and multidimensional scaling, by taking into consideration item difficulty. Utilized in the…
Descriptors: Discriminant Analysis, Factor Analysis, Item Analysis, Matrices
Peer reviewedHiggins, Norma; Rice, Elizabeth – Educational Technology, Research and Development, 1991
Describes a study that was designed to gather information about teachers' perspectives on achievement testing and to describe where the competency-based testing in the CUES (Continuous Uniform Evaluation System) program fits into the teachers' overall plans for teaching and assessing students. Recommendations for instructional design and teacher…
Descriptors: Achievement Tests, Classification, Classroom Observation Techniques, Instructional Design
Peer reviewedJackson, Douglas N.; Helmes, Edward – Applied Psychological Measurement, 1979
A basic structure approach is proposed for obtaining multidimensional scale values for attitude, achievement, or personality items from response data. The technique permits the unconfounding of scale values due to response bias and content and partitions item indices of popularity or difficulty among a number of relevant dimensions. (Author/BH)
Descriptors: Higher Education, Interest Inventories, Item Analysis, Mathematical Models
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