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Claude, ChatGPT, Copilot, and Gemini Performance versus Students in Different Topics of Neuroscience
Peer reviewed
Direct linkVolodymyr 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
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
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
Download full textBrahim 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
Himel Mondal; Juhu Kiran Krushna Karri; Swaminathan Ramasubramanian; Shaikat Mondal; Ayesha Juhi; Pratima Gupta – Advances in Physiology Education, 2025
Large language models (LLMs)-based chatbots use natural language processing and are a type of generative artificial intelligence (AI) that is capable of comprehending user input and generating output in various formats. They offer potential benefits in medical education. This study explored the student's feedback on the utilization of LLMs in…
Descriptors: Computational Linguistics, Physiology, Teaching Methods, Artificial Intelligence
Abdullah Al Fraidan – International Journal of Distance Education Technologies, 2025
This study explores vocabulary assessment practices in Saudi Arabia's hybrid EFL ecosystem, leveraging platforms like Blackboard and Google Forms. The focus is on identifying prevalent test formats and evaluating their alignment with modern pedagogical goals. To classify vocabulary assessment formats in hybridized EFL contexts and recommend the…
Descriptors: Vocabulary Development, English (Second Language), Second Language Learning, Second Language Instruction
Qiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests
