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Kenneth Tyler Wilcox; Ross Jacobucci; Zhiyong Zhang; Brooke A. Ammerman – Grantee Submission, 2023
Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…
Descriptors: Bayesian Statistics, Content Analysis, Undergraduate Students, Self Destructive Behavior
Ayesha Sohail; Huma Akram – Pedagogical Research, 2025
The ability to properly evaluate one's own academic progress has long been considered a predictor of academic success. However, its distinctive role in the context of computational mathematics remains underexplored. Grounded in social cognitive theory, this study investigates the critical role of self-regulated learning (SRL) strategies in…
Descriptors: Undergraduate Students, Mathematics Education, Mathematics Achievement, Self Evaluation (Individuals)
Albert, Jim; Hu, Jingchen – Journal of Statistics Education, 2020
Bayesian statistics has gained great momentum since the computational developments of the 1990s. Gradually, advances in Bayesian methodology and software have made Bayesian techniques much more accessible to applied statisticians and, in turn, have potentially transformed Bayesian education at the undergraduate level. This article provides an…
Descriptors: Bayesian Statistics, Computation, Statistics Education, Undergraduate Students
Hu, Jingchen – Journal of Statistics Education, 2020
We propose a semester-long Bayesian statistics course for undergraduate students with calculus and probability background. We cultivate students' Bayesian thinking with Bayesian methods applied to real data problems. We leverage modern Bayesian computing techniques not only for implementing Bayesian methods, but also to deepen students'…
Descriptors: Bayesian Statistics, Statistics Education, Undergraduate Students, Computation
Hardman, Kyle O.; Cowan, Nelson – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Working memory (WM) is used for storing information in a highly accessible state so that other mental processes, such as reasoning, can use that information. Some WM tasks require that participants not only store information, but also reason about that information to perform optimally on the task. In this study, we used visual WM tasks that had…
Descriptors: Logical Thinking, Short Term Memory, Models, Individual Differences
Kim, Sooyeon; Moses, Tim – ETS Research Report Series, 2016
The purpose of this study is to evaluate the extent to which item response theory (IRT) proficiency estimation methods are robust to the presence of aberrant responses under the "GRE"® General Test multistage adaptive testing (MST) design. To that end, a wide range of atypical response behaviors affecting as much as 10% of the test items…
Descriptors: Item Response Theory, Computation, Robustness (Statistics), Response Style (Tests)
Hall, Stacey; Phang, Sen Han; Schaefer, Jeffrey P.; Ghali, William; Wright, Bruce; McLaughlin, Kevin – Advances in Health Sciences Education, 2014
Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of…
Descriptors: Computation, Probability, Pretests Posttests, Heuristics
Jenny, Mirjam A.; Rieskamp, Jörg; Nilsson, Håkan – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Judging whether multiple events will co-occur is an important aspect of everyday decision making. The underlying probabilities of occurrence are usually unknown and have to be inferred from experience. Using a rigorous, quantitative model comparison, we investigate how people judge the conjunctive probabilities of multiple events to co-occur. In 2…
Descriptors: Experimental Psychology, Decision Making, Probability, Models
Schmidt, Susanne; Zlatkin-Troitschanskaia, Olga; Fox, Jean-Paul – Journal of Educational Measurement, 2016
Longitudinal research in higher education faces several challenges. Appropriate methods of analyzing competence growth of students are needed to deal with those challenges and thereby obtain valid results. In this article, a pretest-posttest-posttest multivariate multilevel IRT model for repeated measures is introduced which is designed to address…
Descriptors: Foreign Countries, Pretests Posttests, Hierarchical Linear Modeling, Item Response Theory
Zwick, Rebecca; Ye, Lei; Isham, Steven – Journal of Educational and Behavioral Statistics, 2012
This study demonstrates how the stability of Mantel-Haenszel (MH) DIF (differential item functioning) methods can be improved by integrating information across multiple test administrations using Bayesian updating (BU). The authors conducted a simulation that showed that this approach, which is based on earlier work by Zwick, Thayer, and Lewis,…
Descriptors: Test Bias, Computation, Statistical Analysis, Bayesian Statistics
Avetisyan, Marianna; Fox, Jean-Paul – Psicologica: International Journal of Methodology and Experimental Psychology, 2012
In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized…
Descriptors: Computation, Sample Size, Responses, Multivariate Analysis
Griffiths, Thomas L.; Tenenbaum, Joshua B. – Journal of Experimental Psychology: General, 2011
Predicting the future is a basic problem that people have to solve every day and a component of planning, decision making, memory, and causal reasoning. In this article, we present 5 experiments testing a Bayesian model of predicting the duration or extent of phenomena from their current state. This Bayesian model indicates how people should…
Descriptors: Bayesian Statistics, Statistical Inference, Models, Prior Learning
Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2013
The usefulness of the l[subscript z] person-fit index was investigated with achievement test data from 20 exams given to more than 3,200 college students. Results for three methods of estimating ? showed that the distributions of l[subscript z] were not consistent with its theoretical distribution, resulting in general overfit to the item response…
Descriptors: Achievement Tests, College Students, Goodness of Fit, Item Response Theory
Teaching an Application of Bayes' Rule for Legal Decision-Making: Measuring the Strength of Evidence
Satake, Eiki; Murray, Amy Vashlishan – Journal of Statistics Education, 2014
Although Bayesian methodology has become a powerful approach for describing uncertainty, it has largely been avoided in undergraduate statistics education. Here we demonstrate that one can present Bayes' Rule in the classroom through a hypothetical, yet realistic, legal scenario designed to spur the interests of students in introductory- and…
Descriptors: Bayesian Statistics, College Mathematics, Mathematics Instruction, Statistics
Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming – Applied Psychological Measurement, 2013
Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…
Descriptors: Item Response Theory, Models, Vertical Organization, Bayesian Statistics
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