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Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
Jianbin Fu; Xuan Tan; Patrick C. Kyllonen – Journal of Educational Measurement, 2024
This paper presents the item and test information functions of the Rank two-parameter logistic models (Rank-2PLM) for items with two (pair) and three (triplet) statements in forced-choice questionnaires. The Rank-2PLM model for pairs is the MUPP-2PLM (Multi-Unidimensional Pairwise Preference) and, for triplets, is the Triplet-2PLM. Fisher's…
Descriptors: Questionnaires, Test Items, Item Response Theory, Models
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
A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
Jiawei Xiong; George Engelhard; Allan S. Cohen – Measurement: Interdisciplinary Research and Perspectives, 2025
It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…
Descriptors: Responses, Test Items, Test Format, Grade 8
Xiaowen Liu – International Journal of Testing, 2024
Differential item functioning (DIF) often arises from multiple sources. Within the context of multidimensional item response theory, this study examined DIF items with varying secondary dimensions using the three DIF methods: SIBTEST, Mantel-Haenszel, and logistic regression. The effect of the number of secondary dimensions on DIF detection rates…
Descriptors: Item Analysis, Test Items, Item Response Theory, Correlation
Xiangyi Liao; Daniel M Bolt – Educational Measurement: Issues and Practice, 2024
Traditional approaches to the modeling of multiple-choice item response data (e.g., 3PL, 4PL models) emphasize slips and guesses as random events. In this paper, an item response model is presented that characterizes both disjunctively interacting guessing and conjunctively interacting slipping processes as proficiency-related phenomena. We show…
Descriptors: Item Response Theory, Test Items, Error Correction, Guessing (Tests)
Kuan-Yu Jin; Wai-Lok Siu – Journal of Educational Measurement, 2025
Educational tests often have a cluster of items linked by a common stimulus ("testlet"). In such a design, the dependencies caused between items are called "testlet effects." In particular, the directional testlet effect (DTE) refers to a recursive influence whereby responses to earlier items can positively or negatively affect…
Descriptors: Models, Test Items, Educational Assessment, Scores
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
Gregory M. Hurtz; Regi Mucino – Journal of Educational Measurement, 2024
The Lognormal Response Time (LNRT) model measures the speed of test-takers relative to the normative time demands of items on a test. The resulting speed parameters and model residuals are often analyzed for evidence of anomalous test-taking behavior associated with fast and poorly fitting response time patterns. Extending this model, we…
Descriptors: Student Reaction, Reaction Time, Response Style (Tests), Test Items
Jochen Ranger; Christoph König; Benjamin W. Domingue; Jörg-Tobias Kuhn; Andreas Frey – Journal of Educational and Behavioral Statistics, 2024
In the existing multidimensional extensions of the log-normal response time (LNRT) model, the log response times are decomposed into a linear combination of several latent traits. These models are fully compensatory as low levels on traits can be counterbalanced by high levels on other traits. We propose an alternative multidimensional extension…
Descriptors: Models, Statistical Distributions, Item Response Theory, Response Rates (Questionnaires)
Martijn Schoenmakers; Jesper Tijmstra; Jeroen Vermunt; Maria Bolsinova – Educational and Psychological Measurement, 2024
Extreme response style (ERS), the tendency of participants to select extreme item categories regardless of the item content, has frequently been found to decrease the validity of Likert-type questionnaire results. For this reason, various item response theory (IRT) models have been proposed to model ERS and correct for it. Comparisons of these…
Descriptors: Item Response Theory, Response Style (Tests), Models, Likert Scales
Güler Yavuz Temel – Journal of Educational Measurement, 2024
The purpose of this study was to investigate multidimensional DIF with a simple and nonsimple structure in the context of multidimensional Graded Response Model (MGRM). This study examined and compared the performance of the IRT-LR and Wald test using MML-EM and MHRM estimation approaches with different test factors and test structures in…
Descriptors: Computation, Multidimensional Scaling, Item Response Theory, Models
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
Stephanie M. Bell; R. Philip Chalmers; David B. Flora – Educational and Psychological Measurement, 2024
Coefficient omega indices are model-based composite reliability estimates that have become increasingly popular. A coefficient omega index estimates how reliably an observed composite score measures a target construct as represented by a factor in a factor-analysis model; as such, the accuracy of omega estimates is likely to depend on correct…
Descriptors: Influences, Models, Measurement Techniques, Reliability
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