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Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
Qusai Khraisha; Sophie Put; Johanna Kappenberg; Azza Warraitch; Kristin Hadfield – Research Synthesis Methods, 2024
Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…
Descriptors: Peer Evaluation, Research Reports, Artificial Intelligence, Computer Software
Arbain – Indonesian Journal of English Language Teaching and Applied Linguistics, 2023
This study aims to investigate the types and functions of expressions of fear realized in the form of sentences. With a special context in horror movies, the researcher attempted to reveal the types and functions of fear expressions such as directive, commissive, expressive, assertive, and declarative. This research focuses on the subtitles of the…
Descriptors: Films, Speech Acts, Accuracy, Fear
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
Hongfei Ye; Jian Xu; Danqing Huang; Meng Xie; Jinming Guo; Junrui Yang; Haiwei Bao; Mingzhi Zhang; Ce Zheng – Discover Education, 2025
This study evaluates Large language models (LLMs)' performance on Chinese Postgraduate Medical Entrance Examination (CPGMEE) as well as the hallucinations produced by LLMs and investigate their implications for medical education. We curated 10 trials of mock CPGMEE to evaluate the performances of 4 LLMs (GPT-4.0, ChatGPT, QWen 2.1 and Ernie 4.0).…
Descriptors: College Entrance Examinations, Foreign Countries, Computational Linguistics, Graduate Medical Education
Jie Zhang – International Journal of Information and Communication Technology Education, 2024
This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing the…
Descriptors: Oral Language, Translation, Computational Linguistics, Computer Software
Xuandong Zhao – ProQuest LLC, 2024
The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…
Descriptors: Computational Linguistics, Intellectual Property, Artificial Intelligence, Productivity
Sümeyra Tosun – Cognitive Research: Principles and Implications, 2024
Machine translation (MT) is the automated process of translating text between different languages, encompassing a wide range of language pairs. This study focuses on non-professional bilingual speakers of Turkish and English, aiming to assess their ability to discern accuracy in machine translations and their preferences regarding MT. A particular…
Descriptors: Bilingualism, Turkish, English (Second Language), Second Language Learning
Yubin Xu; Lin Liu; Jianwen Xiong; Guangtian Zhu – Journal of Baltic Science Education, 2025
As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…
Descriptors: Physics, Artificial Intelligence, Computer Software, Accuracy
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
Kevin C. Haudek; Xiaoming Zhai – International Journal of Artificial Intelligence in Education, 2024
Argumentation, a key scientific practice presented in the "Framework for K-12 Science Education," requires students to construct and critique arguments, but timely evaluation of arguments in large-scale classrooms is challenging. Recent work has shown the potential of automated scoring systems for open response assessments, leveraging…
Descriptors: Accuracy, Persuasive Discourse, Artificial Intelligence, Learning Management Systems
Ibrahim, Karim – Language Testing in Asia, 2023
The release of ChatGPT marked the beginning of a new era of AI-assisted plagiarism that disrupts traditional assessment practices in ESL composition. In the face of this challenge, educators are left with little guidance in controlling AI-assisted plagiarism, especially when conventional methods fail to detect AI-generated texts. One approach to…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
Gautham Arun; Vivek Perumal; Francis Paul John Bato Urias; Yan En Ler; Bryan Wen Tao Tan; Ranganath Vallabhajosyula; Emmanuel Tan; Olivia Ng; Kian Bee Ng; Sreenivasulu Reddy Mogali – Anatomical Sciences Education, 2024
Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and…
Descriptors: Artificial Intelligence, Teaching Methods, Computational Linguistics, Anatomy
Guido Lang; Tamilla Triantoro; Jason H. Sharp – Journal of Information Systems Education, 2024
This study explores the potential of large language models (LLMs), specifically GPT-4 and Gemini, in generating teaching cases for information systems courses. A unique prompt for writing three different types of teaching cases such as a descriptive case, a normative case, and a project-based case on the same IS topic (i.e., the introduction of…
Descriptors: Computational Linguistics, Computer Software, Artificial Intelligence, Readability Formulas
Tatiana Chaiban; Zeinab Nahle; Ghaith Assi; Michelle Cherfane – Discover Education, 2024
Background: Since it was first launched, ChatGPT, a Large Language Model (LLM), has been widely used across different disciplines, particularly the medical field. Objective: The main aim of this review is to thoroughly assess the performance of the distinct version of ChatGPT in subspecialty written medical proficiency exams and the factors that…
Descriptors: Medical Education, Accuracy, Artificial Intelligence, Computer Software