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Becker, Benjamin; Weirich, Sebastian; Goldhammer, Frank; Debeer, Dries – Journal of Educational Measurement, 2023
When designing or modifying a test, an important challenge is controlling its speededness. To achieve this, van der Linden (2011a, 2011b) proposed using a lognormal response time model, more specifically the two-parameter lognormal model, and automated test assembly (ATA) via mixed integer linear programming. However, this approach has a severe…
Descriptors: Test Construction, Automation, Models, Test Items
Michelle Cheong – Journal of Computer Assisted Learning, 2025
Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…
Descriptors: Artificial Intelligence, Performance Based Assessment, Spreadsheets, Models
Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Raykov, Tenko – Measurement: Interdisciplinary Research and Perspectives, 2023
This software review discusses the capabilities of Stata to conduct item response theory modeling. The commands needed for fitting the popular one-, two-, and three-parameter logistic models are initially discussed. The procedure for testing the discrimination parameter equality in the one-parameter model is then outlined. The commands for fitting…
Descriptors: Item Response Theory, Models, Comparative Analysis, Item Analysis
Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2020
This note raises caution that a finding of a marked pseudo-guessing parameter for an item within a three-parameter item response model could be spurious in a population with substantial unobserved heterogeneity. A numerical example is presented wherein each of two classes the two-parameter logistic model is used to generate the data on a…
Descriptors: Guessing (Tests), Item Response Theory, Test Items, Models
Egamaria Alacam; Craig K. Enders; Han Du; Brian T. Keller – Grantee Submission, 2023
Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…
Descriptors: Regression (Statistics), Scores, Psychometrics, Test Items
The Reliability of the Posterior Probability of Skill Attainment in Diagnostic Classification Models
Johnson, Matthew S.; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2020
One common score reported from diagnostic classification assessments is the vector of posterior means of the skill mastery indicators. As with any assessment, it is important to derive and report estimates of the reliability of the reported scores. After reviewing a reliability measure suggested by Templin and Bradshaw, this article suggests three…
Descriptors: Reliability, Probability, Skill Development, Classification
Kim, Kyung Yong – Journal of Educational Measurement, 2020
New items are often evaluated prior to their operational use to obtain item response theory (IRT) item parameter estimates for quality control purposes. Fixed parameter calibration is one linking method that is widely used to estimate parameters for new items and place them on the desired scale. This article provides detailed descriptions of two…
Descriptors: Item Response Theory, Evaluation Methods, Test Items, Simulation
Gao, Xuliang; Ma, Wenchao; Wang, Daxun; Cai, Yan; Tu, Dongbo – Journal of Educational and Behavioral Statistics, 2021
This article proposes a class of cognitive diagnosis models (CDMs) for polytomously scored items with different link functions. Many existing polytomous CDMs can be considered as special cases of the proposed class of polytomous CDMs. Simulation studies were carried out to investigate the feasibility of the proposed CDMs and the performance of…
Descriptors: Cognitive Measurement, Models, Test Items, Scoring
Lawrence T. DeCarlo – Educational and Psychological Measurement, 2024
A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization…
Descriptors: Test Format, Multiple Choice Tests, Item Response Theory, Models
Ravand, Hamdollah; Baghaei, Purya – International Journal of Testing, 2020
More than three decades after their introduction, diagnostic classification models (DCM) do not seem to have been implemented in educational systems for the purposes they were devised. Most DCM research is either methodological for model development and refinement or retrofitting to existing nondiagnostic tests and, in the latter case, basically…
Descriptors: Classification, Models, Diagnostic Tests, Test Construction
Kim, Nana; Bolt, Daniel M. – Educational and Psychological Measurement, 2021
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…
Descriptors: Item Response Theory, Response Style (Tests), Models, Test Items
Carney, Michele B.; Cavey, Laurie; Hughes, Gwyneth – Elementary School Journal, 2017
This article illustrates an argument-based approach to presenting validity evidence for assessment items intended to measure a complex construct. Our focus is developing a measure of teachers' ability to analyze and respond to students' mathematical thinking for the purpose of program evaluation. Our validity argument consists of claims addressing…
Descriptors: Mathematics Instruction, Mathematical Logic, Thinking Skills, Evidence
Russell, Michael – Journal of Applied Testing Technology, 2016
Interest in and use of technology-enhanced items has increased over the past decade. Given the additional time required to administer many technology-enhanced items and the increased expense required to develop them, it is important for testing programs to consider the utility of technology-enhanced items. The Technology-Enhanced Item Utility…
Descriptors: Test Items, Computer Assisted Testing, Models, Fidelity