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Bronson Hui; Zhiyi Wu – Studies in Second Language Acquisition, 2024
A slowdown or a speedup in response times across experimental conditions can be taken as evidence of online deployment of knowledge. However, response-time difference measures are rarely evaluated on their reliability, and there is no standard practice to estimate it. In this article, we used three open data sets to explore an approach to…
Descriptors: Reliability, Reaction Time, Psychometrics, Criticism
Aiman Mohammad Freihat; Omar Saleh Bani Yassin – Educational Process: International Journal, 2025
Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…
Descriptors: Accuracy, Computation, Multiple Choice Tests, Test Items
Mussa Saidi Abubakari; Gamal Abdul Nasir Zakaria; Juraidah Musa – Discover Education, 2025
In the contemporary world of digitalisation, comprehensive digital competence (DC) is and should be an integral part of students' repertoire to guarantee not only academic but also professional success. However, the level and requirements for DC may vary within specific educational contexts, especially in culturally oriented institutions. This…
Descriptors: College Students, Digital Literacy, Student Evaluation, Foreign Countries
Boris Forthmann; Benjamin Goecke; Roger E. Beaty – Creativity Research Journal, 2025
Human ratings are ubiquitous in creativity research. Yet, the process of rating responses to creativity tasks -- typically several hundred or thousands of responses, per rater -- is often time-consuming and expensive. Planned missing data designs, where raters only rate a subset of the total number of responses, have been recently proposed as one…
Descriptors: Creativity, Research, Researchers, Research Methodology
Sean N. Weeks; Tyler L. Renshaw; Allysia A. Rainey; Aubrey Hiatt – Journal of Emotional and Behavioral Disorders, 2024
Internalizing and externalizing problems are common targets for school mental health screening. Prior research supports the interpretation of scores from the Youth Internalizing Problems Screener (YIPS) and the Youth Externalizing Problems Screener (YEPS), which were developed separately yet intended as companion measures. We extended previous…
Descriptors: Adolescents, Screening Tests, Behavior Problems, Mental Health
Lientje Maas; Matthew J. Madison; Matthieu J. S. Brinkhuis – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due…
Descriptors: Clinical Diagnosis, Classification, Models, Psychometrics
Madeline A. Schellman; Matthew J. Madison – Grantee Submission, 2024
Diagnostic classification models (DCMs) have grown in popularity as stakeholders increasingly desire actionable information related to students' skill competencies. Longitudinal DCMs offer a psychometric framework for providing estimates of students' proficiency status transitions over time. For both cross-sectional and longitudinal DCMs, it is…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
Maciej Koscielniak; Jolanta Enko; Agata Gasiorowska – Journal of Academic Ethics, 2024
Examination dishonesty is a global problem that became particularly critical after the outbreak of the COVID-19 pandemic and the shift to remote learning. Academic research has often examined this phenomenon as only one aspect of a broader concept of academic dishonesty and as a one-dimensional construct. This article builds on existing knowledge…
Descriptors: Foreign Countries, Students, Ethics, Cheating
Matthew J. Madison; Stefanie Wind; Lientje Maas; Kazuhiro Yamaguchi; Sergio Haab – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
Matthew J. Madison; Stefanie A. Wind; Lientje Maas; Kazuhiro Yamaguchi; Sergio Haab – Journal of Educational Measurement, 2024
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
Terry A. Ackerman; Deborah L. Bandalos; Derek C. Briggs; Howard T. Everson; Andrew D. Ho; Susan M. Lottridge; Matthew J. Madison; Sandip Sinharay; Michael C. Rodriguez; Michael Russell; Alina A. Davier; Stefanie A. Wind – Educational Measurement: Issues and Practice, 2024
This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational…
Descriptors: Educational Assessment, Competence, Skill Development, Communication Skills
Cornelis Potgieter; Xin Qiao; Akihito Kamata; Yusuf Kara – Grantee Submission, 2024
As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. (2020) estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores,…
Descriptors: Oral Reading, Reading Fluency, Scores, Psychometrics
Cornelis Potgieter; Xin Qiao; Akihito Kamata; Yusuf Kara – Journal of Educational Measurement, 2024
As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores, including…
Descriptors: Oral Reading, Reading Fluency, Scores, Psychometrics

W. Jake Thompson – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…
Descriptors: Bayesian Statistics, Classification, Psychometrics, Goodness of Fit
Miguel Eduardo Uribe-Moreno; Iván Felipe Medina-Arboleda; Alfredo Guzmán-Rincón; Suelen Emilia Castiblanco-Moreno – International Journal of Educational Psychology, 2024
Grit, the passion for achieving long-term goals, has been conceived as a two-dimensional construct (Consistency of interest and Perseverance of effort). The construct is well known for its easy measurement and its relationship with performance, including academic performance. However, there have been different criticisms, such as the overlap of…
Descriptors: Academic Achievement, Psychometrics, Measures (Individuals), Resilience (Psychology)
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