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Gruver, Nate; Malik, Ali; Capoor, Brahm; Piech, Chris; Stevens, Mitchell L.; Paepcke, Andreas – International Educational Data Mining Society, 2019
Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…
Descriptors: Models, Course Selection (Students), Enrollment, Decision Making
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Lamprianou, Iasonas – Educational and Psychological Measurement, 2018
It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as "markers" or "judges") demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new…
Descriptors: Social Networks, Network Analysis, Comparative Analysis, Innovation
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dos Santos, Regina Antunes Teixeira; Gerling, Cristina Capparelli; de Bortoli, Álvaro Luiz – Music Education Research, 2017
A short piano piece was prepared by undergraduate and graduate piano students (N = 15) without guidance from their piano teachers. Temporal parameters were analyzed in several time frames, from a phrase-to-phrase level to an interonset interval. At a macro level, local tempo was shown to be a crucial parameter that divided the students into two…
Descriptors: Undergraduate Students, Musical Instruments, Music Education, Graduate Students
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Grabe, Esther; Kochanski, Greg; Coleman, John – Language and Speech, 2007
The mathematical models of intonation used in speech technology are often inaccessible to linguists. By the same token, phonological descriptions of intonation are rarely used by speech technologists, as they cannot be implemented directly in applications. Consequently, these research communities do not benefit much from each other's insights. In…
Descriptors: Sentences, Intonation, Phonology, Mathematical Models
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Tomizawa, Sadao – Journal of Educational and Behavioral Statistics, 1995
An extended marginal homogeneity model is introduced for the analysis of square contingency tables with the same ordinal row and column classifications. The model hypothesizes that the ratio in each column of table delta will exhibit an exponential function of the column. (SLD)
Descriptors: Classification, Equations (Mathematics), Mathematical Models, Statistical Analysis
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Lienert, G. A.; Krauth, J. – Educational and Psychological Measurement, 1975
Configural frequency analysis (CFA), a new method for identifying types, is illustrated numerically. Relations to latent class analysis and to factor analysis are discussed. It is suggested to use CFA as a type-defining method instead of factor analysis if the variables are linked not only by first but also by higher-order associations. (RC)
Descriptors: Classification, Factor Analysis, Hypothesis Testing, Mathematical Models
Rodger, R. S. – 1974
A fairly large number of different methods exist for evaluating comparisons or null hypothetical contrasts. Because it is difficult to choose among them, this paper develops a 2 by 2 classification of the methods. The first dimension of the classification is decision-based error rate vs. experimentwise error rate. The second dimension is planned…
Descriptors: Classification, Evaluation Methods, Hypothesis Testing, Mathematical Models
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Huberty, Carl J.; Curry, Allen R. – Multivariate Behavioral Research, 1978
Classification is a procedure through which individuals are classified as being members of a particular group based on a variety of independent variables. Two methods of makin such classifications are discussed; the quadratic method is seen to be superior to the linear under certain constraints. (JKS)
Descriptors: Analysis of Covariance, Classification, Discriminant Analysis, Groups
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Heiser, Willem J. – Psychometrika, 2004
Categories can be counted, rated, or ranked, but they cannot be measured. Likewise, persons or individuals can be counted, rated, or ranked, but they cannot be measured either. Nevertheless, psychology has realized early on that it can take an indirect road to measurement: What can be measured is the strength of association between categories in…
Descriptors: Psychometrics, Classification, Sociometric Techniques, Geometric Concepts
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Levin, Joseph – Multivariate Behavioral Research, 1974
Descriptors: Classification, Correlation, Factor Analysis, Mathematical Models
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Lowery, Lawrence F.; Allen, Leslie R. – School Science and Mathematics, 1973
Descriptors: Classification, Elementary School Mathematics, Mathematical Models, Mathematics Education
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Willson, Victor L. – 1975
A theoretical model is developed for analysis of intervention effects in multiple autocorrelated time-series which may be classified or blocked two ways. The intervention effect is estimated independently for each series. The estimates are then entered as observations in two-factor analysis of variance with one observation per cell, utilizing a…
Descriptors: Analysis of Variance, Classification, Correlation, Intervention
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White, Lee J.; And Others – 1975
The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Wurtele, Zivia S. – 1967
The utilization of computer programed mathematical models for educational planning has a brief but rapidly accelerating history. This paper describes and, to some extent, evaluates several of these models. It also discusses some of the theoretical problems associated with their formulation and implementation. Models surveyed are of: (1) the…
Descriptors: Classification, Computer Programs, Cost Effectiveness, Educational Planning
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Burstein, Leigh – Sociological Methods and Research, 1978
Four techniques for assessing differences between least-squares estimators of regression coefficients from group and individual-level data are summarized. The utility and suitability of all four approaches are discussed when (1) data are grouped by a nominal characteristic; (2) there are multiple regressors; or (3) individual-level data cannot be…
Descriptors: Classification, Group Testing, Groups, Higher Education
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