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Hsu, Chia-Ling; Chen, Yi-Hsin; Wu, Yi-Jhen – Practical Assessment, Research & Evaluation, 2023
Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…
Descriptors: Bayesian Statistics, Computation, International Assessment, Achievement Tests
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Owen Henkel; Hannah Horne-Robinson; Maria Dyshel; Greg Thompson; Ralph Abboud; Nabil Al Nahin Ch; Baptiste Moreau-Pernet; Kirk Vanacore – Journal of Learning Analytics, 2025
This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a mathematics learning platform used by middle and high school students in several African countries. Using this dataset, we conducted two experiments to evaluate the use of large language models (LLM) for grading particularly challenging…
Descriptors: Learning Analytics, Learning Management Systems, Mathematics Instruction, Middle School Students
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Lijin Zhang; Xueyang Li; Zhiyong Zhang – Grantee Submission, 2023
The thriving developer community has a significant impact on the widespread use of R software. To better understand this community, we conducted a study analyzing all R packages available on CRAN. We identified the most popular topics of R packages by text mining the package descriptions. Additionally, using network centrality measures, we…
Descriptors: Computer Software, Programming Languages, Data Analysis, Visual Aids
Siebrase, Benjamin – ProQuest LLC, 2018
Multilayer perceptron neural networks, Gaussian naive Bayes, and logistic regression classifiers were compared when used to make early predictions regarding one-year college student persistence. Two iterations of each model were built, utilizing a grid search process within 10-fold cross-validation in order to tune model parameters for optimal…
Descriptors: Classification, College Students, Academic Persistence, Bayesian Statistics
Beck, Melanie Renee – ProQuest LLC, 2018
The large flood of data flowing from observatories presents significant challenges to astronomy and cosmology--challenges that will only be magnified by projects currently under development. Growth in both volume and velocity of astrophysics data is accelerating: whereas the Sloan Digital Sky Survey (SDSS) has produced 60 terabytes of data in the…
Descriptors: Classification, Astronomy, Physics, Measurement
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Chiu, Chia-Yi; Köhn, Hans-Friedrich; Wu, Huey-Min – International Journal of Testing, 2016
The Reduced Reparameterized Unified Model (Reduced RUM) is a diagnostic classification model for educational assessment that has received considerable attention among psychometricians. However, the computational options for researchers and practitioners who wish to use the Reduced RUM in their work, but do not feel comfortable writing their own…
Descriptors: Educational Diagnosis, Classification, Models, Educational Assessment
Lui, Joseph P. – ProQuest LLC, 2013
Identifying appropriate international distributors for small and medium-sized enterprises (SMEs) in the software industry for overseas markets can determine a firm's future endeavors in international expansion. SMEs lack the complex skills in market research and decision analysis to identify suitable partners to engage in global market entry.…
Descriptors: Small Businesses, Computer Software, Bayesian Statistics, Selection
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Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien – Applied Psychological Measurement, 2013
The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…
Descriptors: Computer Assisted Testing, Adaptive Testing, Models, Bayesian Statistics
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Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
Kim, Hyun Seok John – ProQuest LLC, 2011
Cognitive diagnostic assessment (CDA) is a new theoretical framework for psychological and educational testing that is designed to provide detailed information about examinees' strengths and weaknesses in specific knowledge structures and processing skills. During the last three decades, more than a dozen psychometric models have been developed…
Descriptors: Cognitive Measurement, Diagnostic Tests, Bayesian Statistics, Statistical Inference
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DeCarlo, Lawrence T. – Applied Psychological Measurement, 2011
Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…
Descriptors: Bayesian Statistics, Computation, Cognitive Tests, Diagnostic Tests
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Ruscio, John – Assessment, 2009
Determining whether individuals belong to different latent classes (taxa) or vary along one or more latent factors (dimensions) has implications for assessment. For example, no instrument can simultaneously maximize the efficiency of categorical and continuous measurement. Methods such as taxometric analysis can test the relative fit of taxonic…
Descriptors: Classification, Measurement, Measurement Techniques, Evaluation Research
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Rupp, Andre A.; Levy, Roy; Dicerbo, Kristen E.; Sweet, Shauna J.; Crawford, Aaron V.; Calico, Tiago; Benson, Martin; Fay, Derek; Kunze, Katie L.; Mislevy, Robert J.; Behrens, John T. – Journal of Educational Data Mining, 2012
In this paper we describe the development and refinement of "evidence rules" and "measurement models" within the "evidence model" of the "evidence-centered design" (ECD) framework in the context of the "Packet Tracer" digital learning environment of the "Cisco Networking Academy." Using…
Descriptors: Computer Networks, Evidence Based Practice, Design, Instructional Design
Nokelainen, Petri; Ruohotie, Pekka; Tirri, Henry – 1999
Bayesian and classical approaches to classification of vocational data were compared using an educational data set from a longitudinal study of professional growth and development in organizations (P. Ruohotie et al., 1994). Data were from 2,430 workers in companies in Finland who completed a questionnaire with behavior and background statements.…
Descriptors: Bayesian Statistics, Classification, Computer Software, Employment
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries