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Brian E. Clauser; Victoria Yaneva; Peter Baldwin; Le An Ha; Janet Mee – Applied Measurement in Education, 2024
Multiple-choice questions have become ubiquitous in educational measurement because the format allows for efficient and accurate scoring. Nonetheless, there remains continued interest in constructed-response formats. This interest has driven efforts to develop computer-based scoring procedures that can accurately and efficiently score these items.…
Descriptors: Computer Uses in Education, Artificial Intelligence, Scoring, Responses
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Zesch, Torsten; Horbach, Andrea; Zehner, Fabian – Educational Measurement: Issues and Practice, 2023
In this article, we systematize the factors influencing performance and feasibility of automatic content scoring methods for short text responses. We argue that performance (i.e., how well an automatic system agrees with human judgments) mainly depends on the linguistic variance seen in the responses and that this variance is indirectly influenced…
Descriptors: Influences, Academic Achievement, Feasibility Studies, Automation
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Guadalupe Elizabeth Morales-Martinez; Ricardo Jesus Villarreal-Lozano; Maria Isolde Hedlefs-Aguilar – International Journal of Emotional Education, 2025
This research study explored the systematic thinking modes underlying test anxiety in 706 engineering students through an experiment centred on the cognitive algebra paradigm. The participants had to read 36 experimental scenarios that narrated an imaginary academic assessment situation one by one and then judge the level of anxiety they…
Descriptors: Engineering Education, Cognitive Style, College Students, Student Attitudes
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Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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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
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Jessie Leigh Nielsen; Rikke Vang Christensen; Mads Poulsen – Journal of Research in Reading, 2024
Background: Studies of syntactic comprehension and reading comprehension use a wide range of syntactic comprehension tests that vary considerably in format. The goal of this study was to examine to which extent different formats of syntactic comprehension tests measure the same construct. Methods: Sixty-nine Grade 4 students completed multiple…
Descriptors: Syntax, Reading Comprehension, Comparative Analysis, Reading Tests
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Ting Sun; Stella Yun Kim – Educational and Psychological Measurement, 2024
Equating is a statistical procedure used to adjust for the difference in form difficulty such that scores on those forms can be used and interpreted comparably. In practice, however, equating methods are often implemented without considering the extent to which two forms differ in difficulty. The study aims to examine the effect of the magnitude…
Descriptors: Difficulty Level, Data Interpretation, Equated Scores, High School Students
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Skylar J. Laursen; Dorina Sluka; Chris M. Fiacconi – Metacognition and Learning, 2024
Previous literature suggests learners can adjust their encoding strategies to match the demands of the expected test format. However, it is unclear whether other forms of metacognitive control, namely, study time allocation and restudy selection, are also sensitive to expected test format. Across four experiments we examined whether learners…
Descriptors: Test Format, Test Wiseness, Metacognition, Study Habits
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Davis, Sara D.; Chan, Jason C. K. – Educational Psychology Review, 2023
Prior testing can facilitate subsequent learning, a phenomenon termed the forward testing effect (FTE). We examined a metacognitive account of this effect, which proposes that the FTE occurs because retrieval leads to strategy optimizations during later learning. One prediction of this account is that tests that require less retrieval effort…
Descriptors: Metacognition, Futures (of Society), Tests, Difficulty Level
Victoria Crisp; Sylvia Vitello; Abdullah Ali Khan; Heather Mahy; Sarah Hughes – Research Matters, 2025
This research set out to enhance our understanding of the exam techniques and types of written annotations or markings that learners may wish to use to support their thinking when taking digital multiple-choice exams. Additionally, we aimed to further explore issues around the factors that contribute to learners writing less rough work and…
Descriptors: Computer Assisted Testing, Test Format, Multiple Choice Tests, Notetaking
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Vahe Permzadian; Kit W. Cho – Teaching in Higher Education, 2025
When administering an in-class exam, a common decision that confronts every instructor is whether the exam format should be closed book or open book. The present review synthesizes research examining the effect of administering closed-book or open-book assessments on long-term learning. Although the overall effect of assessment format on learning…
Descriptors: College Students, Tests, Test Format, Long Term Memory
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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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Nana Kim; Daniel M. Bolt – Journal of Educational and Behavioral Statistics, 2024
Some previous studies suggest that response times (RTs) on rating scale items can be informative about the content trait, but a more recent study suggests they may also be reflective of response styles. The latter result raises questions about the possible consideration of RTs for content trait estimation, as response styles are generally viewed…
Descriptors: Item Response Theory, Reaction Time, Response Style (Tests), Psychometrics
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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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Choe, Edison M.; Han, Kyung T. – Journal of Educational Measurement, 2022
In operational testing, item response theory (IRT) models for dichotomous responses are popular for measuring a single latent construct [theta], such as cognitive ability in a content domain. Estimates of [theta], also called IRT scores or [theta hat], can be computed using estimators based on the likelihood function, such as maximum likelihood…
Descriptors: Scores, Item Response Theory, Test Items, Test Format
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