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Dimitrov, Dimiter M.; Atanasov, Dimitar V. – Educational and Psychological Measurement, 2022
This study offers an approach to testing for differential item functioning (DIF) in a recently developed measurement framework, referred to as "D"-scoring method (DSM). Under the proposed approach, called "P-Z" method of testing for DIF, the item response functions of two groups (reference and focal) are compared by…
Descriptors: Test Bias, Methods, Test Items, Scoring
Chang, Kuo-Feng – ProQuest LLC, 2022
This dissertation was designed to foster a deeper understanding of population invariance in the context of composite-score equating and provide practitioners with guidelines for addressing score equity concerns at the composite score level. The purpose of this dissertation was threefold. The first was to compare different composite equating…
Descriptors: Test Items, Equated Scores, Methods, Design
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Fu, Yanyan; Choe, Edison M.; Lim, Hwanggyu; Choi, Jaehwa – Educational Measurement: Issues and Practice, 2022
This case study applied the "weak theory" of Automatic Item Generation (AIG) to generate isomorphic item instances (i.e., unique but psychometrically equivalent items) for a large-scale assessment. Three representative instances were selected from each item template (i.e., model) and pilot-tested. In addition, a new analytical framework,…
Descriptors: Test Items, Measurement, Psychometrics, Test Construction
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Daniel Bolt; Yang Caroline Wang; Robert Meyer – Grantee Submission, 2025
Response anchoring, the tendency for respondents to provide item responses equivalent (or in close proximity) to immediately preceding responses, can reflect disengaged responding and/or cognitive challenges in comprehending test items. Using Grade 4-12 student responses to a survey measure of four social-emotional learning constructs collected…
Descriptors: Learner Engagement, Rating Scales, Social Emotional Learning, Item Response Theory
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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
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Hasibe Yahsi Sari; Hulya Kelecioglu – International Journal of Assessment Tools in Education, 2025
The aim of the study is to examine the effect of polytomous item ratio on ability estimation in different conditions in multistage tests (MST) using mixed tests. The study is simulation-based research. In the PISA 2018 application, the ability parameters of the individuals and the item pool were created by using the item parameters estimated from…
Descriptors: Test Items, Test Format, Accuracy, Test Length
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Kylie Gorney; Mark D. Reckase – Journal of Educational Measurement, 2025
In computerized adaptive testing, item exposure control methods are often used to provide a more balanced usage of the item pool. Many of the most popular methods, including the restricted method (Revuelta and Ponsoda), use a single maximum exposure rate to limit the proportion of times that each item is administered. However, Barrada et al.…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Mingfeng Xue; Ping Chen – Journal of Educational Measurement, 2025
Response styles pose great threats to psychological measurements. This research compares IRTree models and anchoring vignettes in addressing response styles and estimating the target traits. It also explores the potential of combining them at the item level and total-score level (ratios of extreme and middle responses to vignettes). Four models…
Descriptors: Item Response Theory, Models, Comparative Analysis, Vignettes
Joshua B. Gilbert; Zachary Himmelsbach; Luke W. Miratrix; Andrew D. Ho; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2025
Value added models (VAMs) attempt to estimate the causal effects of teachers and schools on student test scores. We apply Generalizability Theory to show how estimated VA effects depend upon the selection of test items. Standard VAMs estimate causal effects on the items that are included on the test. Generalizability demands consideration of how…
Descriptors: Value Added Models, Reliability, Effect Size, Test Items
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Owen Henkel; Libby Hills; Bill Roberts; Joshua McGrane – International Journal of Artificial Intelligence in Education, 2025
Formative assessment plays a critical role in improving learning outcomes by providing feedback on student mastery. Open-ended questions, which require students to produce multi-word, nontrivial responses, are a popular tool for formative assessment as they provide more specific insights into what students do and do not know. However, grading…
Descriptors: Artificial Intelligence, Grading, Reading Comprehension, Natural Language Processing
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Mingfeng Xue; Mark Wilson – Applied Measurement in Education, 2024
Multidimensionality is common in psychological and educational measurements. This study focuses on dimensions that converge at the upper anchor (i.e. the highest acquisition status defined in a learning progression) and compares different ways of dealing with them using the multidimensional random coefficients multinomial logit model and scale…
Descriptors: Learning Trajectories, Educational Assessment, Item Response Theory, Evolution
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James D. Weese; Ronna C. Turner; Allison Ames; Xinya Liang; Brandon Crawford – Journal of Experimental Education, 2024
In this study a standardized effect size was created for use with the SIBTEST procedure. Using this standardized effect size, a single set of heuristics was developed that are appropriate for data fitting different item response models (e.g., 2-parameter logistic, 3-parameter logistic). The standardized effect size rescales the raw beta-uni value…
Descriptors: Test Bias, Test Items, Item Response Theory, Effect Size
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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
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Kuan-Yu Jin; Thomas Eckes – Educational and Psychological Measurement, 2024
Insufficient effort responding (IER) refers to a lack of effort when answering survey or questionnaire items. Such items typically offer more than two ordered response categories, with Likert-type scales as the most prominent example. The underlying assumption is that the successive categories reflect increasing levels of the latent variable…
Descriptors: Item Response Theory, Test Items, Test Wiseness, Surveys
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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
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