Name
Focus Session: Enhancing Medical Student Learning through AI-Assisted Wrong Answer Journal Analysis
Presentation Track(s)
AI in Health Professions Education
Description

Medical students often struggle with effective study strategies and may not fully benefit from their mistakes, which can impact their academic performance and long-term professional development. Traditional approaches to addressing these challenges have shown limited success. This session addresses the timely need for innovative, scalable solutions that leverage emerging technologies to enhance student learning outcomes through systematic error analysis.

The integration of AI in medical education is a rapidly evolving field with significant potential to transform how students learn from their mistakes. By exploring AI-supported wrong answer journal analysis, this session addresses the growing need for medical educators to understand and effectively implement AI tools in their curricula. The approach presented combines the power of structured error reflection with personalized, AI-generated study recommendations, offering a novel solution to longstanding challenges in medical education.

This topic is particularly significant given the increasing emphasis on self-directed learning and metacognition in medical education. By focusing on enhancing students' ability to learn from their mistakes and develop targeted study strategies, this approach has the potential to not only improve immediate academic outcomes but also to foster critical skills for long-term professional success and lifelong learning.

Agenda & Methods

  1. Introduction and Overview (10 minutes)
    • Brief presentation on the rationale and potential of AI-supported wrong answer journal analysis in medical education.
  2. Interactive Demonstration (20 minutes)
    • Live demonstration of the wrong answer journal template and AI-generated analysis report.
    • Participants will have the opportunity to interact with the tools in real-time.
  3. Small Group Activity (25 minutes)
    • Participants will be divided into small groups to design a wrong answer journal template based on a sample course topic.
    • Groups will then brainstorm potential AI applications for analyzing student error data.
  4. Large Group Discussion (20 minutes)
    • Groups will share their designs and ideas.
    • Facilitated discussion on the potential benefits and challenges of implementing this approach.
  5. Q&A and Reflection (15 minutes)
    • Open forum for questions and discussion.
    • Participants will reflect on how they might apply these concepts in their own educational settings.
Date & Time
Monday, June 16, 2025, 3:00 PM - 4:30 PM