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Nico Willert; Jonathan Thiemann – Technology, Knowledge and Learning, 2024
Manual composition of tasks and exams is a challenging and time-consuming task. Especially when exams are taken remotely without the personal monitoring by examiners, most exams can easily lose their integrity with the use of previously done exercises or student communication. This research introduces an approach that incorporates the principles…
Descriptors: Tests, Examiners, Foreign Countries, Multiple Choice Tests
Lei Guo; Wenjie Zhou; Xiao Li – Journal of Educational and Behavioral Statistics, 2024
The testlet design is very popular in educational and psychological assessments. This article proposes a new cognitive diagnosis model, the multiple-choice cognitive diagnostic testlet (MC-CDT) model for tests using testlets consisting of MC items. The MC-CDT model uses the original examinees' responses to MC items instead of dichotomously scored…
Descriptors: Multiple Choice Tests, Diagnostic Tests, Accuracy, Computer Software
Claude, ChatGPT, Copilot, and Gemini Performance versus Students in Different Topics of Neuroscience
Volodymyr Mavrych; Ahmed Yaqinuddin; Olena Bolgova – Advances in Physiology Education, 2025
Despite extensive studies on large language models and their capability to respond to questions from various licensed exams, there has been limited focus on employing chatbots for specific subjects within the medical curriculum, specifically medical neuroscience. This research compared the performances of Claude 3.5 Sonnet (Anthropic), GPT-3.5 and…
Descriptors: Artificial Intelligence, Computer Software, Neurosciences, Medical Education
Philip Newton; Maira Xiromeriti – Assessment & Evaluation in Higher Education, 2024
Media coverage suggests that ChatGPT can pass examinations based on multiple choice questions (MCQs), including those used to qualify doctors, lawyers, scientists etc. This poses a potential risk to the integrity of those examinations. We reviewed current research evidence regarding the performance of ChatGPT on MCQ-based examinations in higher…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Integrity, Computer Software
Valentina Albano; Donatella Firmani; Luigi Laura; Jerin George Mathew; Anna Lucia Paoletti; Irene Torrente – Journal of Learning Analytics, 2023
Multiple-choice questions (MCQs) are widely used in educational assessments and professional certification exams. Managing large repositories of MCQs, however, poses several challenges due to the high volume of questions and the need to maintain their quality and relevance over time. One of these challenges is the presence of questions that…
Descriptors: Natural Language Processing, Multiple Choice Tests, Test Items, Item Analysis
Kunal Sareen – Innovations in Education and Teaching International, 2024
This study examines the proficiency of Chat GPT, an AI language model, in answering questions on the Situational Judgement Test (SJT), a widely used assessment tool for evaluating the fundamental competencies of medical graduates in the UK. A total of 252 SJT questions from the "Oxford Assess and Progress: Situational Judgement" Test…
Descriptors: Ethics, Decision Making, Artificial Intelligence, Computer Software
Roger Young; Emily Courtney; Alexander Kah; Mariah Wilkerson; Yi-Hsin Chen – Teaching of Psychology, 2025
Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…
Descriptors: Item Response Theory, Multiple Choice Tests, Psychology, Textbooks
Marli Crabtree; Kenneth L. Thompson; Ellen M. Robertson – HAPS Educator, 2024
Research has suggested that changing one's answer on multiple-choice examinations is more likely to lead to positive academic outcomes. This study aimed to further understand the relationship between changing answer selections and item attributes, student performance, and time within a population of 158 first-year medical students enrolled in a…
Descriptors: Anatomy, Science Tests, Medical Students, Medical Education
Kyeng Gea Lee; Mark J. Lee; Soo Jung Lee – International Journal of Technology in Education and Science, 2024
Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, textbased questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of…
Descriptors: Artificial Intelligence, Computer Software, Biology, Science Instruction
Mickael Antoine Joseph; Jansirani Natarajan; Omar Al Zaabi; Srinivasa Rao Sirasanagandla – Anatomical Sciences Education, 2025
Anatomy and physiology courses are foundational in nursing education but are often perceived as challenging due to heavy content load. Innovative teaching methods, including social media platforms like Instagram Reels, may enhance student engagement and learning. In this quasi-experimental pre-post-test design with a control group, we examined the…
Descriptors: Student Motivation, Anatomy, Physiology, Science Instruction
Emery-Wetherell, Meaghan; Wang, Ruoyao – Assessment & Evaluation in Higher Education, 2023
Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Cheating, Identification
Harun Bayer; Fazilet Gül Ince Araci; Gülsah Gürkan – International Journal of Technology in Education and Science, 2024
The rapid advancement of artificial intelligence technologies, their pervasive use in every field, and the growing understanding of the benefits they bring have led actors in the education sector to pursue research in this field. In particular, the use of artificial intelligence tools has become more prevalent in the education sector due to the…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Technology Uses in Education
Brahim Ait Hammou; Abderrazak Zaafour; Bendaoud Nadif; Mohammed Zemrani – Language Teaching Research Quarterly, 2025
Research on the relationship between vocabulary knowledge and reading has largely focused on literal comprehension of informational texts. The present study, however, investigates the vocabulary-reading relationship by specifically examining critical reading skills in an argumentative text.76 EFL university students majoring in Education and…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Vocabulary Development
Rao, Dhawaleswar; Saha, Sujan Kumar – IEEE Transactions on Learning Technologies, 2020
Automatic multiple choice question (MCQ) generation from a text is a popular research area. MCQs are widely accepted for large-scale assessment in various domains and applications. However, manual generation of MCQs is expensive and time-consuming. Therefore, researchers have been attracted toward automatic MCQ generation since the late 90's.…
Descriptors: Multiple Choice Tests, Test Construction, Automation, Computer Software
Sheng, Yanyan – Measurement: Interdisciplinary Research and Perspectives, 2019
Classical approach to test theory has been the foundation for educational and psychological measurement for over 90 years. This approach concerns with measurement error and hence test reliability, which in part relies on individual test items. The CTT package, developed in light of this, provides functions for test- and item-level analyses of…
Descriptors: Item Response Theory, Test Reliability, Item Analysis, Error of Measurement

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