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Braun, Thorsten; Stierle, Rolf; Fischer, Matthias; Gross, Joachim – Chemical Engineering Education, 2023
Contributing to a competency model for engineering thermodynamics, we investigate the empirical competency structure of our exams in an attempt to answer the question: Do we test the competencies we want to convey to our students? We demonstrate that thermodynamic modeling and mathematical solution emerge as significant dimensions of thermodynamic…
Descriptors: Thermodynamics, Consciousness Raising, Engineering Education, Test Format
Braumoeller, Bear F. – Sociological Methods & Research, 2017
Fuzzy-set qualitative comparative analysis (fsQCA) has become one of the most prominent methods in the social sciences for capturing causal complexity, especially for scholars with small- and medium-"N" data sets. This research note explores two key assumptions in fsQCA's methodology for testing for necessary and sufficient…
Descriptors: Qualitative Research, Comparative Analysis, Social Science Research, Research Methodology
Olsen, Jennifer; Aleven, Vincent; Rummel, Nikol – Journal of Educational Measurement, 2017
Within educational data mining, many statistical models capture the learning of students working individually. However, not much work has been done to extend these statistical models of individual learning to a collaborative setting, despite the effectiveness of collaborative learning activities. We extend a widely used model (the additive factors…
Descriptors: Mathematical Models, Information Retrieval, Data Analysis, Educational Research
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
Cowan, Nelson; Hardman, Kyle; Saults, J. Scott; Blume, Christopher L.; Clark, Katherine M.; Sunday, Mackenzie A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Here we examine a new task to assess working memory for visual arrays in which the participant must judge how many items changed from a studied array to a test array. As a clue to processing, on some trials in the first 2 experiments, participants carried out a metamemory judgment in which they were to decide how many items were in working memory.…
Descriptors: Experimental Psychology, Short Term Memory, Correlation, Performance
Parkavi, A.; Lakshmi, K.; Srinivasa, K. G. – Educational Research and Reviews, 2017
Data analysis techniques can be used to analyze the pattern of data in different fields. Based on the analysis' results, it is recommended that suggestions be provided to decision making authorities. The data mining techniques can be used in educational domain to improve the outcome of the educational sectors. The authors carried out this research…
Descriptors: Data Analysis, Educational Research, Goodness of Fit, Decision Making
Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models
Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning – Journal of Educational and Behavioral Statistics, 2012
The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…
Descriptors: Structural Equation Models, Goodness of Fit, Geometric Concepts, Algebra
Rivera, F. D. – Educational Studies in Mathematics, 2010
In this research article, I present evidence of the existence of visual templates in pattern generalization activity. Such templates initially emerged from a 3-week design-driven classroom teaching experiment on pattern generalization involving linear figural patterns and were assessed for existence in a clinical interview that was conducted four…
Descriptors: Mathematical Concepts, Generalization, Interviews, Models
Mooijaart, Ab; Satorra, Albert – Psychometrika, 2009
In this paper, we show that for some structural equation models (SEM), the classical chi-square goodness-of-fit test is unable to detect the presence of nonlinear terms in the model. As an example, we consider a regression model with latent variables and interactions terms. Not only the model test has zero power against that type of…
Descriptors: Structural Equation Models, Geometric Concepts, Goodness of Fit, Models
Bauer, Daniel J. – Psychometrika, 2009
When using linear models for cluster-correlated or longitudinal data, a common modeling practice is to begin by fitting a relatively simple model and then to increase the model complexity in steps. New predictors might be added to the model, or a more complex covariance structure might be specified for the observations. When fitting models for…
Descriptors: Goodness of Fit, Computation, Models, Predictor Variables
Williams, Thomas O., Jr.; Fall, Anna-Maria; Eaves, Ronald C.; Darch, Craig; Woods-Groves, Suzanne – Assessment for Effective Intervention, 2007
The factor structure of the "KeyMath--Revised Normative Update" (KMR-NU) "Form A" was analyzed using data from a sample of 130 students. The KMR-NU is composed of 13 subtests that are purported to measure three important aspects of math ability: Basic Concepts, Operations, and Applications. A confirmatory factor analysis…
Descriptors: Mathematical Models, Goodness of Fit, Academic Ability, Mathematics

Hernandez, Ana; Gonzalez-Roma, Vicente – Multivariate Behavioral Research, 2002
Studied whether empirical multitrait multioccasion (MTMO) data conform more closely to multiplicative models than to additive models, using four additive models and two versions of the multiplicative Direct Product model. Results based on matrices from previous studies show that both additive and multiplicative models usually fit the same MTMO…
Descriptors: Goodness of Fit, Mathematical Models

MacCallum, Robert C.; Hong, Sehee – Multivariate Behavioral Research, 1997
Procedures are presented for conducting power analyses of tests of overall fit of covariance structure models when null and alternative levels of model fit are specified in terms of values of the GFI or AGFI fit indexes. Reasons the root mean square error of approximation fit index may be preferable are discussed. (SLD)
Descriptors: Goodness of Fit, Mathematical Models, Power (Statistics)
Forster, Fred – 1976
Various factors which influence the relationship between the Rasch item characteristic curve and the actual performance of an item are identified. The Rasch item characteristic curve is a new concept in test design and analysis. The Rasch test model provides information concerning the percent of students with a specified achievement level who…
Descriptors: Goodness of Fit, Item Analysis, Mathematical Models, Probability