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Hyemin Han; Kelsie J. Dawson – Journal of Moral Education, 2024
In the present study, we examined how the perceived attainability and relatability of moral exemplars predicted moral elevation and pleasantness among both adult and college student participants. Data collected from two experiments were analyzed with Bayesian multilevel modeling to explore which factors significantly predicted outcome variables at…
Descriptors: Moral Values, Prediction, Models, Behavior Patterns
Raykov, Tenko; Doebler, Philipp; Marcoulides, George A. – Measurement: Interdisciplinary Research and Perspectives, 2022
This article is concerned with the large-sample parameter estimator behavior in applications of Bayesian confirmatory factor analysis in behavioral measurement. The property of strong convergence of the popular Bayesian posterior median estimator is discussed, which states numerical convergence with probability 1 of the resulting estimates to the…
Descriptors: Bayesian Statistics, Measurement Techniques, Correlation, Factor Analysis
Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2023
Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using…
Descriptors: Cheating, Reaction Time, Test Items, Responses
Giuseppe Arena; Joris Mulder; Roger Th. A. J. Leenders – Sociological Methods & Research, 2024
In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently…
Descriptors: Bayesian Statistics, Social Networks, Memory, Decision Making
Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
Frederick J. Poole; Matthew D. Coss; Jody Clarke-Midura – Language Learning & Technology, 2025
This study explored the use of stealth assessments within a digital game to assess second language (L2) Chinese learners' reading comprehension. Log data tracking learners' in-game behaviors from a game designed for Chinese dual language immersion classrooms (Poole et al., 2022) were used to construct Bayesian Belief Networks to model reading…
Descriptors: Second Language Instruction, Second Language Learning, Reading Comprehension, Game Based Learning
Bezirhan, Ummugul; von Davier, Matthias; Grabovsky, Irina – Educational and Psychological Measurement, 2021
This article presents a new approach to the analysis of how students answer tests and how they allocate resources in terms of time on task and revisiting previously answered questions. Previous research has shown that in high-stakes assessments, most test takers do not end the testing session early, but rather spend all of the time they were…
Descriptors: Response Style (Tests), Accuracy, Reaction Time, Ability
Pavel Chernyavskiy; Traci S. Kutaka; Carson Keeter; Julie Sarama; Douglas Clements – Grantee Submission, 2024
When researchers code behavior that is undetectable or falls outside of the validated ordinal scale, the resultant outcomes often suffer from informative missingness. Incorrect analysis of such data can lead to biased arguments around efficacy and effectiveness in the context of experimental and intervention research. Here, we detail a new…
Descriptors: Bayesian Statistics, Mathematics Instruction, Learning Trajectories, Item Response Theory
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
Lee, HyeSun; Smith, Weldon Z. – Educational and Psychological Measurement, 2020
Based on the framework of testlet models, the current study suggests the Bayesian random block item response theory (BRB IRT) model to fit forced-choice formats where an item block is composed of three or more items. To account for local dependence among items within a block, the BRB IRT model incorporated a random block effect into the response…
Descriptors: Bayesian Statistics, Item Response Theory, Monte Carlo Methods, Test Format
Jing Lu; Chun Wang; Ningzhong Shi – Grantee Submission, 2023
In high-stakes, large-scale, standardized tests with certain time limits, examinees are likely to engage in either one of the three types of behavior (e.g., van der Linden & Guo, 2008; Wang & Xu, 2015): solution behavior, rapid guessing behavior, and cheating behavior. Oftentimes examinees do not always solve all items due to various…
Descriptors: High Stakes Tests, Standardized Tests, Guessing (Tests), Cheating
Whalen, Andrew; Griffiths, Thomas L.; Buchsbaum, Daphna – Cognitive Science, 2018
Social learning has been shown to be an evolutionarily adaptive strategy, but it can be implemented via many different cognitive mechanisms. The adaptive advantage of social learning depends crucially on the ability of each learner to obtain relevant and accurate information from informants. The source of informants' knowledge is a particularly…
Descriptors: Social Development, Socialization, Bayesian Statistics, Behavior Patterns
Pezzulo, Giovanni; Cartoni, Emilio; Rigoli, Francesco; io-Lopez, Léo; Friston, Karl – Learning & Memory, 2016
Balancing habitual and deliberate forms of choice entails a comparison of their respective merits--the former being faster but inflexible, and the latter slower but more versatile. Here, we show that arbitration between these two forms of control can be derived from first principles within an Active Inference scheme. We illustrate our arguments…
Descriptors: Interference (Learning), Epistemology, Physiology, Neurology
Sims, Chris R.; Neth, Hansjorg; Jacobs, Robert A.; Gray, Wayne D. – Psychological Review, 2013
Melioration--defined as choosing a lesser, local gain over a greater longer term gain--is a behavioral tendency that people and pigeons share. As such, the empirical occurrence of meliorating behavior has frequently been interpreted as evidence that the mechanisms of human choice violate the norms of economic rationality. In some environments, the…
Descriptors: Decision Making, Correlation, Learning Experience, Behavior Patterns
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