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Wang, Chao; Lu, Hong – Educational Technology & Society, 2018
This study focused on the effect of examinees' ability levels on the relationship between Reflective-Impulsive (RI) cognitive style and item response time in computerized adaptive testing (CAT). The total of 56 students majoring in Educational Technology from Shandong Normal University participated in this study, and their RI cognitive styles were…
Descriptors: Item Response Theory, Computer Assisted Testing, Cognitive Style, Correlation
Chen, Binglin; West, Matthew; Ziles, Craig – International Educational Data Mining Society, 2018
This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…
Descriptors: Accuracy, Probability, Student Behavior, Test Items
Anselmi, Pasquale; Robusto, Egidio; Stefanutti, Luca – Psychometrika, 2012
The Gain-Loss model is a probabilistic skill multimap model for assessing learning processes. In practical applications, more than one skill multimap could be plausible, while none corresponds to the true one. The article investigates whether constraining the error probabilities is a way of uncovering the best skill assignment among a number of…
Descriptors: Item Response Theory, Learning Processes, Simulation, Probability
Goldin, Ilya M.; Koedinger, Kenneth R.; Aleven, Vincent – International Educational Data Mining Society, 2012
Although ITSs are supposed to adapt to differences among learners, so far, little attention has been paid to how they might adapt to differences in how students learn from help. When students study with an Intelligent Tutoring System, they may receive multiple types of help, but may not comprehend and make use of this help in the same way. To…
Descriptors: Performance Factors, Intelligent Tutoring Systems, Individual Differences, Prediction
Agus, Mirian; Penna, Maria Pietronilla; Peró-Cebollero, Maribel; Guàrdia-Olmos, Joan – EURASIA Journal of Mathematics, Science & Technology Education, 2016
Research on the graphical facilitation of probabilistic reasoning has been characterised by the effort expended to identify valid assessment tools. The authors developed an assessment instrument to compare reasoning performances when problems were presented in verbal-numerical and graphical-pictorial formats. A sample of undergraduate psychology…
Descriptors: Probability, Abstract Reasoning, Thinking Skills, Educational Assessment
Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas – Multivariate Behavioral Research, 2011
The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…
Descriptors: Monte Carlo Methods, Patients, Probability, Item Response Theory
Rakes, Christopher R. – ProQuest LLC, 2010
In this study, the author examined the relationship of probability misconceptions to algebra, geometry, and rational number misconceptions and investigated the potential of probability instruction as an intervention to address misconceptions in all 4 content areas. Through a review of literature, 5 fundamental concepts were identified that, if…
Descriptors: Control Groups, Fundamental Concepts, Intervention, Structural Equation Models
Mislevy, Robert J.; Huang, Chun-Wei – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2006
Advances in cognitive research increase the need for assessment that can address the processes and the strategies by which persons solve problems. Several psychometric models have been introduced to handle claims cast in information-processing terms, explicitly modeling performance in terms of theory-based predictions of performance. Cognitively…
Descriptors: Cognitive Science, Cognitive Processes, Problem Solving, Psychometrics
Kreiner, Svend; Hansen, Mogens; Hansen, Carsten Rosenberg – Applied Psychological Measurement, 2006
Mixed Rasch models add latent classes to conventional Rasch models, assuming that the Rasch model applies within each class and that relative difficulties of items are different in two or more latent classes. This article considers a family of stochastically ordered mixed Rasch models, with ordinal latent classes characterized by increasing total…
Descriptors: Item Response Theory, Cognitive Tests, Problem Solving, Statistical Analysis
Sideridis, Georgios D. – Educational Psychology, 2007
Research in goal theory has often relied on the general linear model, ignoring some central assumptions of the theoretical framework under investigation. The purpose of the two studies reported here was to illustrate how the Rasch model can supplement traditional statistical analyses when evaluating the effects of goal orientations on persistence.…
Descriptors: Persistence, Probability, Item Response Theory, Data Analysis

Mislevy, Robert J.; Verhelst, Norman – Psychometrika, 1990
A model is presented for item responses when different subjects use different strategies, but only responses--not choice of strategy--can be observed. Substantive theory is used to differentiate the likelihoods of response vectors under a fixed set of strategies, and response probabilities are modeled via item parameters for each strategy. (TJH)
Descriptors: Algorithms, Guessing (Tests), Item Response Theory, Mathematical Models