Actively Recruiting
An AI Educational Agent for Medical Machine Learning Courses
Led by Sun Yat-sen University · Updated on 2026-03-05
56
Participants Needed
1
Research Sites
47 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
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.
CONDITIONS
Official Title
An AI Educational Agent for Medical Machine Learning Courses
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Medical graduate students from universities in the Guangdong-Hong Kong-Macao Greater Bay Area
- Graduate students enrolled in the "Machine Learning and Data Mining" course
- Completed prerequisite courses: "Medical Statistics" and "Nursing Research"
- Able to operate the AI Educational Agent system and willing to participate in teaching interventions and assessments
You will not qualify if you...
- Unwilling to use the AI education agent system or refuse data collection
- Unable to commit to the full course duration or have scheduling conflicts
- Previously enrolled in or audited this course in prior academic years
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
North Campus of Sun Yat-sen University
Guangzhou, Guangdong, China, 510000
Actively Recruiting
Research Team
W
Wei Xia, PhD
CONTACT
J
Jiebing Luo
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
NA
Model
SINGLE_GROUP
Primary Purpose
OTHER
Number of Arms
1
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