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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
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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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Ulrike Padó; Yunus Eryilmaz; Larissa Kirschner – International Journal of Artificial Intelligence in Education, 2024
Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…
Descriptors: Grading, Automation, Test Format, Computer Assisted Testing
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Chang, Minyu; Brainerd, C. J. – Metacognition and Learning, 2023
Making judgments of learning (JOLs) can sometimes modify subsequent memory performance, which is referred to as JOL reactivity. We evaluated two major theoretical explanations of JOL reactivity and used the dual-retrieval model to pinpoint the retrieval processes that are modified by JOLs. The changed-goal hypothesis assumes that JOLs highlight…
Descriptors: Cues, Evaluative Thinking, Models, Recall (Psychology)
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Anna Filighera; Sebastian Ochs; Tim Steuer; Thomas Tregel – International Journal of Artificial Intelligence in Education, 2024
Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However,…
Descriptors: Cheating, Grading, Form Classes (Languages), Computer Software
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Cerullo, Enzo; Jones, Hayley E.; Carter, Olivia; Quinn, Terry J.; Cooper, Nicola J.; Sutton, Alex J. – Research Synthesis Methods, 2022
Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of…
Descriptors: Meta Analysis, Test Format, Medicine, Standards
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Wilson, Joseph; Pollard, Benjamin; Aiken, John M.; Lewandowski, H. J. – Physical Review Physics Education Research, 2022
Surveys have long been used in physics education research to understand student reasoning and inform course improvements. However, to make analysis of large sets of responses practical, most surveys use a closed-response format with a small set of potential responses. Open-ended formats, such as written free response, can provide deeper insights…
Descriptors: Natural Language Processing, Science Education, Physics, Artificial Intelligence
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Sahu, Archana; Bhowmick, Plaban Kumar – IEEE Transactions on Learning Technologies, 2020
In this paper, we studied different automatic short answer grading (ASAG) systems to provide a comprehensive view of the feature spaces explored by previous works. While the performance reported in previous works have been encouraging, systematic study of the features is lacking. Apart from providing systematic feature space exploration, we also…
Descriptors: Automation, Grading, Test Format, Artificial Intelligence
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Huang, Hung-Yu – Educational and Psychological Measurement, 2023
The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs)…
Descriptors: Test Items, Classification, Bayesian Statistics, Decision Making
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Stephane E. Collignon; Josey Chacko; Salman Nazir – Journal of Information Systems Education, 2024
Most business schools require students to take at least one technical Management Information System (MIS) course. Due to the technical nature of the material, the course and the assessments tend to be anxiety inducing. With over three out of every five students in US colleges suffering from "overwhelming anxiety" in some form, we study…
Descriptors: Multiple Choice Tests, Test Format, Business Schools, Information Systems
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Kim, Kyung Yong; Lim, Euijin; Lee, Won-Chan – International Journal of Testing, 2019
For passage-based tests, items that belong to a common passage often violate the local independence assumption of unidimensional item response theory (UIRT). In this case, ignoring local item dependence (LID) and estimating item parameters using a UIRT model could be problematic because doing so might result in inaccurate parameter estimates,…
Descriptors: Item Response Theory, Equated Scores, Test Items, Models
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Ippel, Lianne; Magis, David – Educational and Psychological Measurement, 2020
In dichotomous item response theory (IRT) framework, the asymptotic standard error (ASE) is the most common statistic to evaluate the precision of various ability estimators. Easy-to-use ASE formulas are readily available; however, the accuracy of some of these formulas was recently questioned and new ASE formulas were derived from a general…
Descriptors: Item Response Theory, Error of Measurement, Accuracy, Standards
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Trendtel, Matthias; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
A multidimensional Bayesian item response model is proposed for modeling item position effects. The first dimension corresponds to the ability that is to be measured; the second dimension represents a factor that allows for individual differences in item position effects called persistence. This model allows for nonlinear item position effects on…
Descriptors: Bayesian Statistics, Item Response Theory, Test Items, Test Format
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Yilmaz, Haci Bayram – International Electronic Journal of Elementary Education, 2019
Open ended and multiple choice questions are commonly placed on the same tests; however, there is a discussion on the effects of using different item types on the test and item statistics. This study aims to compare model and item fit statistics in a mixed format test where multiple choice and constructed response items are used together. In this…
Descriptors: Item Response Theory, Models, Goodness of Fit, Elementary School Science
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