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Designing Self-Directed Learning Content for Medical Students: An AI-Driven Evaluation of Learning Outcomes
Roshni Agarwal1, Amit Kumar1, Vaibhav Agarwal2
1Microbiology, Autonomous State Medical College, Kanpur Dehat, IND.
Cureus
|August 14, 2026
Summary
Generative artificial intelligence (AI) significantly improved self-directed learning (SDL) for medical students, enhancing content quality and knowledge acquisition. Human oversight remains crucial for responsible AI integration in medical education.
Area of Science:
- Medical Education
- Artificial Intelligence in Healthcare
- Competency-Based Medical Education
Background:
- India's National Medical Commission mandates self-directed learning (SDL) within the MBBS curriculum.
- Generative AI tools offer potential for enhancing SDL but raise concerns regarding accuracy and academic integrity.
- This study investigates the impact of an organized AI-assisted SDL process on undergraduate medical students.
Purpose of the Study:
- To assess the quality and effectiveness of AI-assisted SDL compared to traditional SDL.
- To evaluate the impact of AI-assisted SDL on medical students' knowledge acquisition and learning outcomes.
- To explore student perceptions and challenges associated with using AI in SDL.
Main Methods:
- A pre-post interventional trial with a within-subject crossover design involving 83 second-year MBBS students.
- Students received training in prompt engineering and AI verification techniques before undertaking standard and AI-assisted SDL assignments.
- Assignment quality was evaluated using a 10-domain rubric; knowledge acquisition, task completion time, and student opinions were also recorded.
Main Results:
- AI-assisted SDL significantly outperformed traditional SDL across all rubric domains (p < 0.001), with a 29.1% improvement in mean scores.
- Knowledge scores increased significantly (p < 0.001), and average task completion time decreased by 43%.
- Most students reported increased confidence and faster information synthesis, while common challenges included accuracy concerns and formulation time.
Conclusions:
- Systematic integration of generative AI in SDL substantially enhances learning efficiency, knowledge acquisition, and content quality for MBBS students.
- Findings support the integration of AI literacy and verification skills into the medical curriculum.
- Maintaining human oversight is essential for ensuring accurate and responsible AI use in medical education.
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