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Direct linkYimin Ning; Wenjun Zhang; Dengming Yao; Bowen Fang; Binyan Xu; Tommy Tanu Wijaya – Education and Information Technologies, 2025
The integration of AI in education highlights the significance of Teachers' AI Literacy (TAIL). Existing assessment tools, however, are hindered by incomplete indicators and a lack of practicality for large-scale application, necessitating a more systematic and credible evaluation method. This study is based on a systematic literature review and…
Descriptors: Artificial Intelligence, Rating Scales, Technological Literacy, Factor Analysis
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
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
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
Download full textMimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
Bin Zou; Sitian Xie; Chenghao Wang – International Journal of Information and Communication Technology Education, 2025
Willingness to Communicate (WTC) plays a crucial role in developing students' speaking proficiency in English as a Foreign Language (EFL) learning. This study investigates whether students' in-class WTC can be enhanced through an AI-supported program and explores their perceptions of using the AI for future academic speaking development. A…
Descriptors: Artificial Intelligence, Computer Software, Speech Communication, Classroom Communication
