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Showing 1 to 15 of 30 results Save | Export
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Vatsalan, Dinusha; Rakotoarivelo, Thierry; Bhaskar, Raghav; Tyler, Paul; Ladjal, Djazia – British Journal of Educational Technology, 2022
With Big Data revolution, the education sector is being reshaped. The current data-driven education system provides many opportunities to utilize the enormous amount of collected data about students' activities and performance for personalized education, adapting teaching methods, and decision making. On the other hand, such benefits come at a…
Descriptors: Privacy, Risk, Data, Markov Processes
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Agarwal, Deepak; Baker, Ryan S.; Muraleedharan, Anupama – International Educational Data Mining Society, 2020
There has been considerable interest in techniques for modelling student learning across practice problems to drive real-time adaptive learning, with particular focus on variants of the classic Bayesian Knowledge Tracing (BKT) model proposed by Corbett & Anderson, 1995. Over time researches have proposed many variants of BKT with…
Descriptors: Intelligent Tutoring Systems, Models, Skill Development, Mastery Learning
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Zhan, Peida; Jiao, Hong; Man, Kaiwen; Wang, Lijun – Journal of Educational and Behavioral Statistics, 2019
In this article, we systematically introduce the just another Gibbs sampler (JAGS) software program to fit common Bayesian cognitive diagnosis models (CDMs) including the deterministic inputs, noisy "and" gate model; the deterministic inputs, noisy "or" gate model; the linear logistic model; the reduced reparameterized unified…
Descriptors: Bayesian Statistics, Computer Software, Models, Test Items
Gin, Brian; Sim, Nicholas; Skrondal, Anders; Rabe-Hesketh, Sophia – Grantee Submission, 2020
We propose a dyadic Item Response Theory (dIRT) model for measuring interactions of pairs of individuals when the responses to items represent the actions (or behaviors, perceptions, etc.) of each individual (actor) made within the context of a dyad formed with another individual (partner). Examples of its use include the assessment of…
Descriptors: Item Response Theory, Generalization, Item Analysis, Problem Solving
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McNeish, Daniel – Educational and Psychological Measurement, 2017
In behavioral sciences broadly, estimating growth models with Bayesian methods is becoming increasingly common, especially to combat small samples common with longitudinal data. Although Mplus is becoming an increasingly common program for applied research employing Bayesian methods, the limited selection of prior distributions for the elements of…
Descriptors: Models, Bayesian Statistics, Statistical Analysis, Computer Software
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Hoernle, Nicholas; Gal, Kobi; Grosz, Barbara; Protopapas, Pavlos; Rubin, Andee – International Educational Data Mining Society, 2018
Simulations that combine real world components with interactive digital media provide a rich setting for students with the potential to assist knowledge building and understanding of complex physical processes. This paper addresses the problem of modeling the effects of multiple students' simultaneous interactions on the complex and exploratory…
Descriptors: Computer Simulation, Student Behavior, Interaction, Markov Processes
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Halpern, David; Tubridy, Shannon; Wang, Hong Yu; Gasser, Camille; Popp, Pamela Osborn; Davachi, Lila; Gureckis, Todd M. – International Educational Data Mining Society, 2018
Knowledge tracing is a popular and successful approach to modeling student learning. In this paper we investigate whether the addition of neuroimaging observations to a knowledge tracing model enables accurate prediction of memory performance in held-out data. We propose a Hidden Markov Model of memory acquisition related to Bayesian Knowledge…
Descriptors: Learning Processes, Memory, Prediction, Second Language Learning
Zhang, Zhiyong – Grantee Submission, 2016
Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is…
Descriptors: Bayesian Statistics, Models, Statistical Distributions, Computation
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Geigle, Chase; Zhai, ChengXiang – Journal of Educational Data Mining, 2017
Massive open online courses (MOOCs) provide educators with an abundance of data describing how students interact with the platform, but this data is highly underutilized today. This is in part due to the lack of sophisticated tools to provide interpretable and actionable summaries of huge amounts of MOOC activity present in log data. To address…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
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Rafferty, Anna N.; LaMar, Michelle M.; Griffiths, Thomas L. – Cognitive Science, 2015
Watching another person take actions to complete a goal and making inferences about that person's knowledge is a relatively natural task for people. This ability can be especially important in educational settings, where the inferences can be used for assessment, diagnosing misconceptions, and providing informative feedback. In this paper, we…
Descriptors: Inferences, Knowledge Level, Educational Games, Computer Simulation
Sweet, Tracy M. – Journal of Educational and Behavioral Statistics, 2015
Social networks in education commonly involve some form of grouping, such as friendship cliques or teacher departments, and blockmodels are a type of statistical social network model that accommodate these grouping or blocks by assuming different within-group tie probabilities than between-group tie probabilities. We describe a class of models,…
Descriptors: Social Networks, Statistical Analysis, Probability, Models
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Li, Feiming; Cohen, Allan; Bottge, Brian; Templin, Jonathan – Educational and Psychological Measurement, 2016
Latent transition analysis (LTA) was initially developed to provide a means of measuring change in dynamic latent variables. In this article, we illustrate the use of a cognitive diagnostic model, the DINA model, as the measurement model in a LTA, thereby demonstrating a means of analyzing change in cognitive skills over time. An example is…
Descriptors: Statistical Analysis, Change, Thinking Skills, Measurement
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Blazquez, Maite; Budria, Santiago – Education Economics, 2012
In this paper, we use the 2000-2008 waves of the German Socioeconomic Panel to examine overeducation transitions. The results are based on a first-order Markov model that allows us to account for both the initial conditions problem and potential endogeneity in attrition. We found that overeducation dynamics, especially the probability of entering…
Descriptors: Educational Attainment, Overachievement, Education Work Relationship, Personality Traits
Rindskopf, David; Shadish, William; Hedges, Larry – Society for Research on Educational Effectiveness, 2012
Data from single case designs (SCDs) have traditionally been analyzed by visual inspection rather than statistical models. As a consequence, effect sizes have been of little interest. Lately, some effect-size estimators have been proposed, but most are either (i) nonparametric, and/or (ii) based on an analogy incompatible with effect sizes from…
Descriptors: Intervention, Effect Size, Bayesian Statistics, Research Design
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Koskinen, Johan; Stenberg, Sten-Ake – Journal of Educational and Behavioral Statistics, 2012
When studying educational aspirations of adolescents, it is unrealistic to assume that the aspirations of pupils are independent of those of their friends. Considerable attention has also been given to the study of peer influence in the educational and behavioral literature. Typically, in empirical studies, the friendship networks have either been…
Descriptors: Foreign Countries, Bayesian Statistics, Models, Friendship
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