AI teaching assistant for a graduate medical machine learning course

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This non-randomized interventional study will deploy a Knowledge Graph–enhanced LLM-based educational agent as a teaching assistant for Masters and PhD students enrolled in a Machine Learning and Data Mining course at Sun Yat-sen University. The 2025–2026 cohort using the AI agent will be compared to a historical 2024–2025 cohort that received standard instruction, with primary outcomes including academic performance, practical coding ability, and academic self-efficacy. Secondary outcomes include student satisfaction, cognitive engagement, and feasibility of integrating the agent into the curriculum. The agent will provide real-time answers, personalized study plans, and code support throughout the course.

Why it matters

Who can join: the full rules

Inclusion Criteria:

1. Medical graduate students from universities in the Guangdong-Hong Kong-Macao Greater Bay Area;
2. Graduate students who have taken the "Machine Learning and Data Mining" course;
3. Have completed the required prerequisite courses: "Medical Statistics" and "Nursing Research";
4. Capable of operating the AI Educational Agent system normally and willing to undergo relevant teaching interventions and assessments during the study period.

Exclusion Criteria:

1. Unwilling to use the AI education agent system, or refusing to allow the research team to collect their relevant data;
2. Students who cannot commit to the full duration of the course or have known scheduling conflicts that would prevent regular attendance;
3. Students who have previously enrolled in or audited this course in prior academic years to avoid learning effect bias

Where it's running

• North Campus of Sun Yat-sen University
  Guangzhou, Guangdong, China Recruiting

Study contacts

• Study coordinator: Wei Xia, PhD
• Email: xiaw23@mail.sysu.edu.cn
• Phone: 8618823359471

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.