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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
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
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)
Imelu G. Mordeno; Queeneh T. Piape; Art Guilleane R. Roño; Wendel Ann C. Abejar; Michelle Anne L. Ferolino; Norman B. Mendoza – Journal of Psychoeducational Assessment, 2024
The Kessler Psychological Distress Scale (K-10) is widely utilized to assess non-specific psychological distress. However, when applied to COVID-19 pandemic experiences, its psychometric properties have not been examined. This study investigated the factor structure, reliability, and latent profile of K-10 using data from 3032 Filipino teachers…
Descriptors: COVID-19, Profiles, Pandemics, Psychological Patterns
Kaj Sparle Christensen; Ole Jakob Storebø; Bo Bach – Journal of Attention Disorders, 2025
Objective: This study examines the validity of the ASRS-5 as a new screening tool for ADHD and evaluates its proposed screening cut-off in a general population context. Method: A nationally representative sample of 2,002 individuals aged 18 to 80 years was surveyed using the ASRS-5, with complete data obtained from 714 participants. Psychometric…
Descriptors: Foreign Countries, Construct Validity, Psychometrics, Item Analysis
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