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Daniel McNeish – Grantee Submission, 2023
Factor analysis is often used to model scales created to measure latent constructs, and internal structure validity evidence is commonly assessed with indices like SRMR, RMSEA, and CFI. These indices are essentially effect size measures and definitive benchmarks regarding which values connote reasonable fit have been elusive. Simulations from the…
Descriptors: Models, Testing, Indexes, Factor Analysis
Amy Adair – ProQuest LLC, 2024
Developing models, using mathematics, and constructing explanations are three practices essential for science inquiry learning according to education reform efforts, such as the Next Generation Science Standards (NGSS Lead States, 2013). However, students struggle with these intersecting practices, especially when developing and interpreting…
Descriptors: Artificial Intelligence, Evaluation Methods, Scaffolding (Teaching Technique), Mathematics
Fahd, Kiran; Venkatraman, Sitalakshmi; Miah, Shah J.; Ahmed, Khandakar – Education and Information Technologies, 2022
Recently, machine learning (ML) has evolved and finds its application in higher education (HE) for various data analysis. Studies have shown that such an emerging field in educational technology provides meaningful insights into several dimensions of educational quality. An in-depth analysis of the application of ML could have a positive impact on…
Descriptors: Artificial Intelligence, Electronic Learning, Higher Education, Academic Achievement
Hosseinzadeh, Mostafa – ProQuest LLC, 2021
In real-world situations, multidimensional data may appear on large-scale tests or attitudinal surveys. A simple structure, multidimensional model may be used to evaluate the items, ignoring the cross-loading of some items on the secondary dimension. The purpose of this study was to investigate the influence of structure complexity magnitude of…
Descriptors: Item Response Theory, Models, Simulation, Evaluation Methods
Gardner, Josh; Brooks, Christopher – Journal of Learning Analytics, 2018
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…
Descriptors: Prediction, Models, Evaluation, Evaluation Methods
Thiem, Alrik – Sociological Methods & Research, 2015
In a recent contribution to "Sociological Methods & Research," Baumgartner and Epple (B&E) employ Coincidence Analysis (CNA) to explain the outcome of the vote on the Swiss minaret initiative of 2009. Although the authors also present a substantive argument, their principal objective is to prove the superiority of CNA over…
Descriptors: Qualitative Research, Causal Models, Evaluation Methods, Differences
Martin-Fernandez, Manuel; Revuelta, Javier – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…
Descriptors: Bayesian Statistics, Item Response Theory, Models, Comparative Analysis
Capuano, Nicola; Loia, Vincenzo; Orciuoli, Francesco – IEEE Transactions on Learning Technologies, 2017
Massive Open Online Courses (MOOCs) are becoming an increasingly popular choice for education but, to reach their full extent, they require the resolution of new issues like assessing students at scale. A feasible approach to tackle this problem is peer assessment, in which students also play the role of assessor for assignments submitted by…
Descriptors: Participative Decision Making, Models, Peer Evaluation, Online Courses
Martori, Francesc; Cuadros, Jordi; González-Sabaté, Lucinio – International Educational Data Mining Society, 2015
Student modeling can help guide the behavior of a cognitive tutor system and provide insight to researchers on understanding how students learn. In this context, Bayesian Knowledge Tracing (BKT) is one of the most popular knowledge inference models due to its predictive accuracy, interpretability and ability to infer student knowledge. However,…
Descriptors: Bayesian Statistics, Inferences, Prediction, Accuracy
Cai, Xiao – ProQuest LLC, 2013
With the development of PC, internet as well as mobile devices, we are facing a data exploding era. On one hand, more and more features can be collected to describe the data, making the size of the data descriptor larger and larger. On the other hand, the number of data itself explodes and can be collected from multiple resources. When the data…
Descriptors: Data Analysis, Mathematics, Graphs, Regression (Statistics)
Ostrow, Korinn; Donnelly, Chistopher; Heffernan, Neil – International Educational Data Mining Society, 2015
As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…
Descriptors: Intelligent Tutoring Systems, Scoring, Testing, Credits
González-Brenes, José P.; Huang, Yun – International Educational Data Mining Society, 2015
Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…
Descriptors: Intelligent Tutoring Systems, Evaluation Methods, Program Evaluation, Student Behavior
Isenberg, Eric; Hock, Heinrich – Mathematica Policy Research, Inc., 2012
This report describes the value-added models used as part of teacher evaluation systems in the District of Columbia Public Schools (DCPS) and in eligible DC charter schools participating in "Race to the Top." The authors estimated: (1) teacher effectiveness in DCPS and eligible DC charter schools during the 2011-2012 school year; and (2)…
Descriptors: Teacher Evaluation, Value Added Models, Public Schools, Charter Schools
Keselman, H. J.; Miller, Charles W.; Holland, Burt – Psychological Methods, 2011
There have been many discussions of how Type I errors should be controlled when many hypotheses are tested (e.g., all possible comparisons of means, correlations, proportions, the coefficients in hierarchical models, etc.). By and large, researchers have adopted familywise (FWER) control, though this practice certainly is not universal. Familywise…
Descriptors: Validity, Statistical Significance, Probability, Computation
Brusco, Michael; Steinley, Douglas – Psychological Methods, 2010
Structural balance theory (SBT) has maintained a venerable status in the psychological literature for more than 5 decades. One important problem pertaining to SBT is the approximation of structural or generalized balance via the partitioning of the vertices of a signed graph into "K" clusters. This "K"-balance partitioning problem also has more…
Descriptors: Psychology, Mathematical Models, Stimuli, Measurement Techniques