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Leonidas Zotos; Hedderik van Rijn; Malvina Nissim – International Educational Data Mining Society, 2025
In an educational setting, an estimate of the difficulty of Multiple-Choice Questions (MCQs), a commonly used strategy to assess learning progress, constitutes very useful information for both teachers and students. Since human assessment is costly from multiple points of view, automatic approaches to MCQ item difficulty estimation are…
Descriptors: Multiple Choice Tests, Test Items, Difficulty Level, Artificial Intelligence
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Junhuan Wei; Qin Wang; Buyun Dai; Yan Cai; Dongbo Tu – Journal of Educational Measurement, 2024
Traditional IRT and IRTree models are not appropriate for analyzing the item that simultaneously consists of multiple-choice (MC) task and constructed-response (CR) task in one item. To address this issue, this study proposed an item response tree model (called as IRTree-MR) to accommodate items that contain different response types at different…
Descriptors: Item Response Theory, Models, Multiple Choice Tests, Cognitive Processes
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Séverin Lions; María Paz Blanco; Pablo Dartnell; Carlos Monsalve; Gabriel Ortega; Julie Lemarié – Applied Measurement in Education, 2024
Multiple-choice items are universally used in formal education. Since they should assess learning, not test-wiseness or guesswork, they must be constructed following the highest possible standards. Hundreds of item-writing guides have provided guidelines to help test developers adopt appropriate strategies to define the distribution and sequence…
Descriptors: Test Construction, Multiple Choice Tests, Guidelines, Test Items
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Rita Arfi Astuti Ningroom; Sri Yamtinah; Riyadi – Journal of Education and Learning (EduLearn), 2025
There are a lot of very interesting scientific concepts to learn in natural and social science. The initial concepts that the student possesses may contradict the actual concepts, which is what causes misconceptions. Misconceptions are identified using misconception detection test tools. In fact, the development of the use of diagnostic test…
Descriptors: Foreign Countries, Test Construction, Diagnostic Tests, Multiple Choice Tests
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Kentaro Fukushima; Nao Uchida; Kensuke Okada – Journal of Educational and Behavioral Statistics, 2025
Diagnostic tests are typically administered in a multiple-choice (MC) format due to their advantages of objectivity and time efficiency. The MC-deterministic input, noisy "and" gate (DINA) family of models, a representative class of cognitive diagnostic models for MC items, efficiently and parsimoniously estimates the mastery profiles of…
Descriptors: Diagnostic Tests, Cognitive Measurement, Multiple Choice Tests, Educational Assessment
Kala Krishna; Pelin Akyol; Esma Ozer – National Bureau of Economic Research, 2025
Exams are designed to rank students objectively by their abilities, including elements such as time limits, the number and difficulty of questions, and negative marking policies. Using data from a lab-in-field experiment, we develop and estimate a model of student behavior in multiple-choice exams that incorporates the effects of time constraints…
Descriptors: Multiple Choice Tests, Student Behavior, Response Style (Tests), Time
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Stefanie A. Wind; Yuan Ge – Measurement: Interdisciplinary Research and Perspectives, 2024
Mixed-format assessments made up of multiple-choice (MC) items and constructed response (CR) items that are scored using rater judgments include unique psychometric considerations. When these item types are combined to estimate examinee achievement, information about the psychometric quality of each component can depend on that of the other. For…
Descriptors: Interrater Reliability, Test Bias, Multiple Choice Tests, Responses
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Janet Mee; Ravi Pandian; Justin Wolczynski; Amy Morales; Miguel Paniagua; Polina Harik; Peter Baldwin; Brian E. Clauser – Advances in Health Sciences Education, 2024
Recent advances in automated scoring technology have made it practical to replace multiple-choice questions (MCQs) with short-answer questions (SAQs) in large-scale, high-stakes assessments. However, most previous research comparing these formats has used small examinee samples testing under low-stakes conditions. Additionally, previous studies…
Descriptors: Multiple Choice Tests, High Stakes Tests, Test Format, Test Items
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Bilal Ghanem; Alona Fyshe – International Educational Data Mining Society, 2024
Multiple choice questions (MCQs) are a common way to assess reading comprehension. Every MCQ needs a set of distractor answers that are incorrect, but plausible enough to test student knowledge. However, good distractors are hard to create. Distractor generation (DG) models have been proposed, and their performance is typically evaluated using…
Descriptors: Multiple Choice Tests, Reading Comprehension, Test Items, Testing
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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
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David Hope; David Kluth; Matthew Homer; Avril Dewar; Rikki Goddard-Fuller; Alan Jaap; Helen Cameron – Advances in Health Sciences Education, 2025
Rasch modelling is a powerful tool for evaluating item performance, measuring drift in difficulty over time, and comparing students who sat assessments at different times or at different sites. Here, we use data from thirty UK medical schools to describe the benefits of Rasch modelling in quality assurance and the barriers to using it. Sixty…
Descriptors: Item Response Theory, Medical Schools, Foreign Countries, Quality Assurance
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Kashinath Boral; Krishna Kanta Mondal – Journal of Educational Technology Systems, 2025
This study evaluates the performance of three leading AI chatbots--OpenAI's ChatGPT, Google's Gemini, and Microsoft Bing Copilot--in answering multiple choice questions (MCQs) from the UGC-NET Education paper. Using 150 randomly selected questions from examination cycles between June 2019 and December 2023, the chatbots' accuracy was assessed…
Descriptors: Artificial Intelligence, Technology Uses in Education, Multiple Choice Tests, Program Effectiveness
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Brent A. Stevenor; Nadine LeBarron McBride; Charles Anyanwu – Journal of Applied Testing Technology, 2025
Enemy items are two test items that should not be presented to a candidate on the same test. Identifying enemies is essential for personnel assessment, as they weaken the measurement precision and validity of a test. In this research, we examined the effectiveness of lexical and semantic natural language processing techniques for identifying enemy…
Descriptors: Test Items, Natural Language Processing, Occupational Tests, Test Construction
Sherwin E. Balbuena – Online Submission, 2024
This study introduces a new chi-square test statistic for testing the equality of response frequencies among distracters in multiple-choice tests. The formula uses the information from the number of correct answers and wrong answers, which becomes the basis of calculating the expected values of response frequencies per distracter. The method was…
Descriptors: Multiple Choice Tests, Statistics, Test Validity, Testing
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Jessica D. Kotik; Merilee McCurdy; Christopher H. Skinner; Chelsea S. Wilson; Valerie E. Hogan-Sandi; Catherine Smith; Brian E. Wilhoit – Psychology in the Schools, 2025
Inclusive Postsecondary Education programs are designed to provide students with disabilities the opportunity to seek postsecondary education while receiving explicit instruction and support in social and emotional, independent living, and vocational skills. While students enroll in college classes, there is little research available for how to…
Descriptors: Students with Disabilities, Intellectual Disability, Developmental Disabilities, Intervention
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