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Joseph A. Rios; Jiayi Deng – Educational and Psychological Measurement, 2025
To mitigate the potential damaging consequences of rapid guessing (RG), a form of noneffortful responding, researchers have proposed a number of scoring approaches. The present simulation study examines the robustness of the most popular of these approaches, the unidimensional effort-moderated (EM) scoring procedure, to multidimensional RG (i.e.,…
Descriptors: Scoring, Guessing (Tests), Reaction Time, Item Response Theory
Kim, Stella Yun; Lee, Won-Chan – Applied Measurement in Education, 2023
This study evaluates various scoring methods including number-correct scoring, IRT theta scoring, and hybrid scoring in terms of scale-score stability over time. A simulation study was conducted to examine the relative performance of five scoring methods in terms of preserving the first two moments of scale scores for a population in a chain of…
Descriptors: Scoring, Comparative Analysis, Item Response Theory, Simulation
Zwick, Rebecca; Ye, Lei; Isham, Steven – Journal of Educational Measurement, 2018
In typical differential item functioning (DIF) assessments, an item's DIF status is not influenced by its status in previous test administrations. An item that has shown DIF at multiple administrations may be treated the same way as an item that has shown DIF in only the most recent administration. Therefore, much useful information about the…
Descriptors: Test Bias, Testing, Test Items, Bayesian Statistics
Tingir, Seyfullah – ProQuest LLC, 2019
Educators use various statistical techniques to explain relationships between latent and observable variables. One way to model these relationships is to use Bayesian networks as a scoring model. However, adjusting the conditional probability tables (CPT-parameters) to fit a set of observations is still a challenge when using Bayesian networks. A…
Descriptors: Bayesian Statistics, Statistical Analysis, Scoring, Probability
Foster, Colin – International Journal of Science and Mathematics Education, 2022
Confidence assessment (CA) involves students stating alongside each of their answers a confidence rating (e.g. 0 low to 10 high) to express how certain they are that their answer is correct. Each student's score is calculated as the sum of the confidence ratings on the items that they answered correctly, minus the sum of the confidence ratings on…
Descriptors: Mathematics Tests, Mathematics Education, Secondary School Students, Meta Analysis
Magliano, Joseph P.; Lampi, Jodi P.; Ray, Melissa; Chan, Greta – Grantee Submission, 2020
Coherent mental models for successful comprehension require inferences that establish semantic "bridges" between discourse constituents and "elaborations" that incorporate relevant background knowledge. While it is established that individual differences in the extent to which postsecondary students engage in these processes…
Descriptors: Reading Comprehension, Reading Strategies, Inferences, Reading Tests
Liu, Yang; Yang, Ji Seung – Journal of Educational and Behavioral Statistics, 2018
The uncertainty arising from item parameter estimation is often not negligible and must be accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is particularly so when the calibration sample size is limited and/or the calibration IRT model is complex. In the current work, we treat two-stage IRT scoring as a…
Descriptors: Intervals, Scores, Item Response Theory, Bayesian Statistics
Cui, Yang; Chu, Man-Wai; Chen, Fu – Journal of Educational Data Mining, 2019
Digital game-based assessments generate student process data that is much more difficult to analyze than traditional assessments. The formative nature of game-based assessments permits students, through applying and practicing the targeted knowledge and skills during gameplay, to gain experiences, receive immediate feedback, and as a result,…
Descriptors: Educational Games, Student Evaluation, Data Analysis, Bayesian Statistics
Wu, Mike; Davis, Richard L.; Domingue, Benjamin W.; Piech, Chris; Goodman, Noah – International Educational Data Mining Society, 2020
Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…
Descriptors: Item Response Theory, Accuracy, Data Analysis, Public Policy
Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry – ETS Research Report Series, 2015
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Descriptors: Item Response Theory, Computation, Statistical Bias, Error of Measurement
Nicole B. Kersting; Bruce L. Sherin; James W. Stigler – Educational and Psychological Measurement, 2014
In this study, we explored the potential for machine scoring of short written responses to the Classroom-Video-Analysis (CVA) assessment, which is designed to measure teachers' usable mathematics teaching knowledge. We created naïve Bayes classifiers for CVA scales assessing three different topic areas and compared computer-generated scores to…
Descriptors: Scoring, Automation, Video Technology, Teacher Evaluation
McDermott, Paul A.; Watkins, Marley W.; Rhoad, Anna M.; Chao, Jessica L.; Worrell, Frank C.; Hall, Tracey E. – International Journal of School & Educational Psychology, 2015
Given relevant cultural distinctions across nations, it is important to determine the dimensional structure and normative characteristics of psychological assessment devices in each focal population. This article examines the national standardization and validation of the Adjustment Scales for Children and Adolescents (ASCA) with a nationally…
Descriptors: Foreign Countries, Children, Adolescents, Adjustment (to Environment)
He, Wei; Wolfe, Edward W. – Educational and Psychological Measurement, 2012
In administration of individually administered intelligence tests, items are commonly presented in a sequence of increasing difficulty, and test administration is terminated after a predetermined number of incorrect answers. This practice produces stochastically censored data, a form of nonignorable missing data. By manipulating four factors…
Descriptors: Individual Testing, Intelligence Tests, Test Items, Test Length
Suh, Hongwook – ProQuest LLC, 2010
Response time has been regarded as an important source for investigating the relationship between human performance and response speed. It is important to examine the relationship between response time and item characteristics, especially in the perspective of the relationship between response time and various factors that affect examinee's…
Descriptors: Bayesian Statistics, Computation, Reaction Time, Item Response Theory
Kieftenbeld, Vincent; Natesan, Prathiba; Eddy, Colleen – Journal of Psychoeducational Assessment, 2011
The mathematics teaching efficacy beliefs of preservice elementary teachers have been the subject of several studies. A widely used measure in these studies is the Mathematics Teaching Efficacy Beliefs Instrument (MTEBI). The present study provides a detailed analysis of the psychometric properties of the MTEBI using Bayesian item response theory.…
Descriptors: Item Response Theory, Bayesian Statistics, Mathematics Instruction, Preservice Teachers

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