Condition: Medical Education · Artificial Intelligence in Medicine · Sponsor: Sun Yat-sen University
The goal of this interventional study is to evaluate the effectiveness of a Large Language Model (LLM)-based educational AI Agent in graduate students (Masters and PhD) specializing in medicine or nursing who are enrolled in the "Machine Learning and Data Mining" course. The main questions it aims to answer are: Does the use of an educational AI Agent improve students' academic performance and practical skills in machine learning compared to traditional methods? Does the AI intervention enhance students' learning confidence, satisfaction, and cognitive engagement? Researchers will compare students currently using the AI Agent (experimental group) to a historical control group (students from the previous cohort who did not use the AI tool) to see if the AI-assisted learning model leads to significantly higher learning achievements and better educational experiences. Participants will: Utilize the Teaching Agent for real-time answers to theoretical questions, personalized study planning, and knowledge reinforcement. Engage with the Research Agent to assist with literature reviews, research design optimization, and academic writing structure. Use the Practice Innovation Agent for guidance on coding, algorithm debugging, and applying machine learning models to medical data analysis projects.
This description comes directly from the study's public registry record.
Wei Xia, PhD · 8618823359471 · xiaw23@mail.sysu.edu.cn
Jiebing Luo · 8618885639072 · luojiebing2002@163.com
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| North Campus of Sun Yat-sen University | Guangzhou, Guangdong, China | Recruiting |
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Source record: clinicaltrials.gov/study/NCT07449182