Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 4 |
| Since 2007 (last 20 years) | 14 |
Descriptor
| Bayesian Statistics | 15 |
| Evaluation | 15 |
| Models | 15 |
| Comparative Analysis | 4 |
| Computation | 4 |
| Item Response Theory | 4 |
| Decision Making | 3 |
| Experiments | 3 |
| Hypothesis Testing | 3 |
| Prediction | 3 |
| Probability | 3 |
| More ▼ | |
Source
Author
| Alicia M. Chen | 1 |
| Andrew Palacci | 1 |
| Andrew, Megan | 1 |
| Brooks, Christopher | 1 |
| Choi, Kilchan | 1 |
| Craigmile, Peter F. | 1 |
| Erdfelder, Edgar | 1 |
| Gardner, Josh | 1 |
| Geerlings, Hanneke | 1 |
| Gelman, Andrew | 1 |
| Glas, Cees A. W. | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 14 |
| Reports - Research | 8 |
| Reports - Evaluative | 4 |
| Opinion Papers | 1 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 2 |
Audience
Location
| Missouri | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| National Assessment of… | 1 |
What Works Clearinghouse Rating
Alicia M. Chen; Andrew Palacci; Natalia Vélez; Robert D. Hawkins; Samuel J. Gershman – Cognitive Science, 2024
How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N…
Descriptors: Bayesian Statistics, Models, Teaching Methods, Evaluation
Heidemanns, Merlin; Gelman, Andrew; Morris, G. Elliott – Grantee Submission, 2020
During modern general election cycles, information to forecast the electoral outcome is plentiful. So-called fundamentals like economic growth provide information early in the cycle. Trial-heat polls become informative closer to Election Day. Our model builds on (Linzer, 2013) and is implemented in Stan (Team, 2020). We improve on the estimation…
Descriptors: Evaluation, Bayesian Statistics, Elections, Presidents
Mahmud, Jumailiyah – Educational Research and Reviews, 2017
With the development in computing technology, item response theory (IRT) develops rapidly, and has become a user friendly application in psychometrics world. Limitation in classical theory is one aspect that encourages the use of IRT. In this study, the basic concept of IRT will be discussed. In addition, it will briefly review the ability…
Descriptors: Item Response Theory, Fundamental Concepts, Maximum Likelihood Statistics, Psychometrics
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
Wills, Andy J.; Pothos, Emmanuel M. – Psychological Bulletin, 2012
Vanpaemel and Lee (2012) argued, and we agree, that the comparison of formal models can be facilitated by Bayesian methods. However, Bayesian methods neither precede nor supplant our proposals (Wills & Pothos, 2012), as Bayesian methods can be applied both to our proposals and to their polar opposites. Furthermore, the use of Bayesian methods to…
Descriptors: Classification, Bayesian Statistics, Models, Comparative Analysis
Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas – Psychometrika, 2011
A new observable consequence of the property of invariant item ordering is presented, which holds under Mokken's double monotonicity model for dichotomous data. The observable consequence is an invariant ordering of the item-total regressions. Kendall's measure of concordance "W" and a weighted version of this measure are proposed as measures for…
Descriptors: Item Response Theory, Bayesian Statistics, Regression (Statistics), Models
Geerlings, Hanneke; Glas, Cees A. W.; van der Linden, Wim J. – Psychometrika, 2011
An application of a hierarchical IRT model for items in families generated through the application of different combinations of design rules is discussed. Within the families, the items are assumed to differ only in surface features. The parameters of the model are estimated in a Bayesian framework, using a data-augmented Gibbs sampler. An obvious…
Descriptors: Simulation, Intelligence Tests, Item Response Theory, Models
Craigmile, Peter F.; Peruggia, Mario; Van Zandt, Trisha – Psychometrika, 2010
Human response time (RT) data are widely used in experimental psychology to evaluate theories of mental processing. Typically, the data constitute the times taken by a subject to react to a succession of stimuli under varying experimental conditions. Because of the sequential nature of the experiments there are trends (due to learning, fatigue,…
Descriptors: Reaction Time, Models, Experimental Psychology, Stimuli
Hilbig, Benjamin E.; Erdfelder, Edgar; Pohl, Rudiger F. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2011
A new process model of the interplay between memory and judgment processes was recently suggested, assuming that retrieval fluency--that is, the speed with which objects are recognized--will determine inferences concerning such objects in a single-cue fashion. This aspect of the fluency heuristic, an extension of the recognition heuristic, has…
Descriptors: Stimuli, Heuristics, Memory, Goodness of Fit
Klauer, Karl Christoph – Psychometrika, 2010
Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…
Descriptors: Simulation, Bayesian Statistics, Computation, Models
Andrew, Megan; Hauser, Robert M. – Social Forces, 2011
Sociologists have long used educational expectations to understand the complex mental processes underlying individuals' educational decision making. Yet, little research evaluates how students actually formulate their educational expectations. Status attainment theory asserts that students adopt their educational expectations early based on family…
Descriptors: Learning Theories, Grade Point Average, Family Characteristics, Academic Achievement
Rouder, Jeffrey N.; Yue, Yu; Speckman, Paul L.; Pratte, Michael S.; Province, Jordan M. – Psychological Review, 2010
A dominant theme in modeling human perceptual judgments is that sensory neural activity is summed or integrated until a critical bound is reached. Such models predict that, in general, the shape of response time distributions change across conditions, although in practice, this shape change may be subtle. An alternative view is that response time…
Descriptors: Reaction Time, Decision Making, Models, Statistical Analysis
Choi, Kilchan; Seltzer, Michael – Journal of Educational and Behavioral Statistics, 2010
In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a period of substantive interest relate to differences in subsequent change. In this article, the authors present a fully Bayesian approach to estimating three-level Hierarchical Models in which latent…
Descriptors: Simulation, Computation, Models, Bayesian Statistics
Hoffman, Bobby; Schraw, Gregory – Educational Psychologist, 2010
The purpose of this article is to clarify conceptions, definitions, and applications of learning and problem-solving efficiency. Conceptions of efficiency vary within the field of educational psychology, and there is little consensus as to how to define, measure, and interpret the efficiency construct. We compare three diverse models that differ…
Descriptors: Educational Psychology, Efficiency, Problem Solving, Models
Educational Testing Service, Princeton, NJ. – 1971
The conference theme was "The Promise and Perils of Educational Information Systems," defined as collections of test data on knowledges, skills, interests, and attitudes maintained for the purpose of educational decision making. Topics covered were: "Longer Education: Thinner, Broader, or Higher" (Fritz Machlup); "Testing:…
Descriptors: Bayesian Statistics, Bias, Blacks, Conferences

Peer reviewed
Direct link
