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Showing 1 to 15 of 164 results Save | Export
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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)
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Belzak, William C. M. – Educational Measurement: Issues and Practice, 2023
Test developers and psychometricians have historically examined measurement bias and differential item functioning (DIF) across a single categorical variable (e.g., gender), independently of other variables (e.g., race, age, etc.). This is problematic when more complex forms of measurement bias may adversely affect test responses and, ultimately,…
Descriptors: Test Bias, High Stakes Tests, Artificial Intelligence, Test Items
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Dihao Leng; Ummugul Bezirhan; Lale Khorramdel; Bethany Fishbein; Matthias von Davier – Educational Measurement: Issues and Practice, 2024
This study capitalizes on response and process data from the computer-based TIMSS 2019 Problem Solving and Inquiry tasks to investigate gender differences in test-taking behaviors and their association with mathematics achievement at the eighth grade. Specifically, a recently proposed hierarchical speed-accuracy-revisits (SAR) model was adapted to…
Descriptors: Gender Differences, Test Wiseness, Achievement Tests, Mathematics Tests
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Yanyan Fu – Educational Measurement: Issues and Practice, 2024
The template-based automated item-generation (TAIG) approach that involves template creation, item generation, item selection, field-testing, and evaluation has more steps than the traditional item development method. Consequentially, there is more margin for error in this process, and any template errors can be cascaded to the generated items.…
Descriptors: Error Correction, Automation, Test Items, Test Construction
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Folger, Timothy D.; Bostic, Jonathan; Krupa, Erin E. – Educational Measurement: Issues and Practice, 2023
Validity is a fundamental consideration of test development and test evaluation. The purpose of this study is to define and reify three key aspects of validity and validation, namely test-score interpretation, test-score use, and the claims supporting interpretation and use. This study employed a Delphi methodology to explore how experts in…
Descriptors: Test Interpretation, Scores, Test Use, Test Validity
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Guher Gorgun; Okan Bulut – Educational Measurement: Issues and Practice, 2025
Automatic item generation may supply many items instantly and efficiently to assessment and learning environments. Yet, the evaluation of item quality persists to be a bottleneck for deploying generated items in learning and assessment settings. In this study, we investigated the utility of using large-language models, specifically Llama 3-8B, for…
Descriptors: Artificial Intelligence, Quality Control, Technology Uses in Education, Automation
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Berenbon, Rebecca F.; McHugh, Bridget C. – Educational Measurement: Issues and Practice, 2023
To assemble a high-quality test, psychometricians rely on subject matter experts (SMEs) to write high-quality items. However, SMEs are not typically given the opportunity to provide input on which content standards are most suitable for multiple-choice questions (MCQs). In the present study, we explored the relationship between perceived MCQ…
Descriptors: Test Items, Multiple Choice Tests, Standards, Difficulty Level
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Student, Sanford R.; Gong, Brian – Educational Measurement: Issues and Practice, 2022
We address two persistent challenges in large-scale assessments of the Next Generation Science Standards: (a) the validity of score interpretations that target the standards broadly and (b) how to structure claims for assessments of this complex domain. The NGSS pose a particular challenge for specifying claims about students that evidence from…
Descriptors: Science Tests, Test Validity, Test Items, Test Construction
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Steedle, Jeffrey T.; Cho, Young Woo; Wang, Shichao; Arthur, Ann M.; Li, Dongmei – Educational Measurement: Issues and Practice, 2022
As testing programs transition from paper to online testing, they must study mode comparability to support the exchangeability of scores from different testing modes. To that end, a series of three mode comparability studies was conducted during the 2019-2020 academic year with examinees randomly assigned to take the ACT college admissions exam on…
Descriptors: College Entrance Examinations, Computer Assisted Testing, Scores, Test Format
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Zhang, Susu; Li, Anqi; Wang, Shiyu – Educational Measurement: Issues and Practice, 2023
In computer-based tests allowing revision and reviews, examinees' sequence of visits and answer changes to questions can be recorded. The variable-length revision log data introduce new complexities to the collected data but, at the same time, provide additional information on examinees' test-taking behavior, which can inform test development and…
Descriptors: Computer Assisted Testing, Test Construction, Test Wiseness, Test Items
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Jung Yeon Park; Sean Joo; Zikun Li; Hyejin Yoon – Educational Measurement: Issues and Practice, 2025
This study examines potential assessment bias based on students' primary language status in PISA 2018. Specifically, multilingual (MLs) and nonmultilingual (non-MLs) students in the United States are compared with regard to their response time as well as scored responses across three cognitive domains (reading, mathematics, and science).…
Descriptors: Achievement Tests, Secondary School Students, International Assessment, Test Bias
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Kim, Sooyeon; Walker, Michael E. – Educational Measurement: Issues and Practice, 2022
Test equating requires collecting data to link the scores from different forms of a test. Problems arise when equating samples are not equivalent and the test forms to be linked share no common items by which to measure or adjust for the group nonequivalence. Using data from five operational test forms, we created five pairs of research forms for…
Descriptors: Ability, Tests, Equated Scores, Testing Problems
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Stephen G. Sireci; Javier Suárez-Álvarez; April L. Zenisky; Maria Elena Oliveri – Educational Measurement: Issues and Practice, 2024
The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-in-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this article, we lay the foundation for DIRTy…
Descriptors: Educational Assessment, Student Needs, Test Format, Test Construction
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Xuelan Qiu; Jimmy de la Torre; You-Gan Wang; Jinran Wu – Educational Measurement: Issues and Practice, 2024
Multidimensional forced-choice (MFC) items have been found to be useful to reduce response biases in personality assessments. However, conventional scoring methods for the MFC items result in ipsative data, hindering the wider applications of the MFC format. In the last decade, a number of item response theory (IRT) models have been developed,…
Descriptors: Item Response Theory, Personality Traits, Personality Measures, Personality Assessment
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An, Lily Shiao; Ho, Andrew Dean; Davis, Laurie Laughlin – Educational Measurement: Issues and Practice, 2022
Technical documentation for educational tests focuses primarily on properties of individual scores at single points in time. Reliability, standard errors of measurement, item parameter estimates, fit statistics, and linking constants are standard technical features that external stakeholders use to evaluate items and individual scale scores.…
Descriptors: Documentation, Scores, Evaluation Methods, Longitudinal Studies
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