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Kim, Yunsung; Sreechan; Piech, Chris; Thille, Candace – International Educational Data Mining Society, 2023
Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instructional systems to actively monitor the evolution of learner proficiency in real time, existing dynamic item response models rely on expensive inference algorithms that…
Descriptors: Item Response Theory, Accuracy, Inferences, Algorithms
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
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
Jing Ouyang; Gongjun Xu – Grantee Submission, 2022
Latent class models with covariates are widely used for psychological, social, and educational research. Yet the fundamental identifiability issue of these models has not been fully addressed. Among the previous research on the identifiability of latent class models with covariates, Huang and Bandeen-Roche (Psychometrika 69:5-32, 2004) studied the…
Descriptors: Item Response Theory, Models, Identification, Psychological Studies
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
Ge, Yuan – ProQuest LLC, 2022
My dissertation research explored responder behaviors (e.g., demonstrating response styles, carelessness, and possessing misconceptions) that compromise psychometric quality and impact the interpretation and use of assessment results. Identifying these behaviors can help researchers understand and minimize their potentially construct-irrelevant…
Descriptors: Test Wiseness, Response Style (Tests), Item Response Theory, Psychometrics
Ben Stenhaug; Ben Domingue – Grantee Submission, 2022
The fit of an item response model is typically conceptualized as whether a given model could have generated the data. We advocate for an alternative view of fit, "predictive fit", based on the model's ability to predict new data. We derive two predictive fit metrics for item response models that assess how well an estimated item response…
Descriptors: Goodness of Fit, Item Response Theory, Prediction, Models
Carol Eckerly; Yue Jia; Paul Jewsbury – ETS Research Report Series, 2022
Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Scoring
Rajendra Chattergoon – ProQuest LLC, 2020
Learning progressions (LPs) are "descriptions of the successively more sophisticated ways of thinking about a topic that can follow one another as children learn about and investigate a topic over a broad span of time" (National Research Council, 2007). One challenge that arises in LP research is the collection of evidence to ensure that…
Descriptors: Item Response Theory, Models, Validity, Learning Processes
Shah, Meetal Jaswant – ProQuest LLC, 2018
Significant attention is being paid to how assessments aligned to learning trajectories (LTs) can be used as a means to locate students' progress in learning big ideas in mathematics over time. Furthermore, data from LT-aligned assessments have been signaled as key to driving student-centered instruction on a day-to-day basis. For LTs and…
Descriptors: Grade 8, Middle School Students, Validity, Models
Mohammed Alqabbaa – ProQuest LLC, 2021
Psychometricians at an organization named the Education and Training Evaluation Commission (ETEC) developed a new test scoring method called the latent D-scoring method (DSM-L) where it is believed that the new method itself is much easier and more efficient to use compared to the Item Response Theory (IRT) method. However, there are no studies…
Descriptors: Item Response Theory, Scoring, Item Analysis, Equated Scores
Elizabeth Talbott; Andres De Los Reyes; Devin M. Kearns; Jeannette Mancilla-Martinez; Mo Wang – Exceptional Children, 2023
Evidence-based assessment (EBA) requires that investigators employ scientific theories and research findings to guide decisions about what domains to measure, how and when to measure them, and how to make decisions and interpret results. To implement EBA, investigators need high-quality assessment tools along with evidence-based processes. We…
Descriptors: Evidence Based Practice, Evaluation Methods, Special Education, Educational Research
The Choice between Cognitive Diagnosis and Item Response Theory: A Case Study from Medical Education
Youn Seon Lim; Catherine Bangeranye – International Journal of Testing, 2024
Feedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students' current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished.…
Descriptors: Cognitive Measurement, Diagnostic Tests, Item Response Theory, Case Studies