LLMs in Medical School: A New Era of Learning

Can technology shoulder some of the cognitive burden that medical students face?

Reviewed by Abigail Fagan

Key points

• About 68% of medical students use LLMs, and 56% find them accurate for general medical topics.
• LLMs offer personalized learning by adapting to individual needs, improving flexibility for students.
• AI may reduce the cognitive burden, allowing students to focus on higher-order skills like critical thinking.

Medical school is difficult. But there might be a cognitive light at the end of the long corridors of academia.

A recent study at the University of Florida College of Medicine revealed some interesting insights into how medical students are incorporating large language models (LLMs) like ChatGPT into their education. With 67.7% of students using LLMs and 55.9% finding them accurate for general medical topics, the study seems to indicate a growing confidence in AI's role in medical education.

Personalized Learning With LLMs

While the study highlights medical students' positive perceptions of LLMs, it's important to consider the potential for LLMs to go beyond just answering questions. They could provide personalized learning experiences by adapting to each student's style, pace, and language needs. This would allow students to tailor their learning based on time constraints or proficiency levels—a feature that could be a game-changer for time-strapped medical students.

However, the study also reveals that 73.5% of students cross-check LLM responses, reflecting a cautious but necessary approach to ensure accuracy. Although cross-checking might introduce additional effort, it also underscores the evolving relationship between students and AI. As these tools become more trusted and accurate, students may increasingly rely on them, reducing the cognitive load of verification and allowing LLMs to act as more seamless partners in education.

Reimagining the Cognitive Burden in Medical Education

Beyond personalizing education, LLMs offer another transformative opportunity—reducing the cognitive burden placed on students. Medical education today requires an immense mental effort to memorize, integrate, and apply vast amounts of information, much of which is increasing at a pace beyond human capacity to fully assimilate. This heavy cognitive load leaves little room for critical thinking and problem-solving. However, AI can alleviate this by handling more mechanical aspects of learning, allowing students to focus on the art of medicine—the humanistic and intuitive side of patient care.

The study suggests that this shift is already underway. With 22.5% of students using LLMs in clinical settings, it’s clear that LLMs are finding practical applications beyond just learning. AI's role could evolve into a clinical collaborator—sorting through complex data sets, making real-time inferences, and providing decision-making support—allowing future physicians to exercise judgment and empathy without being bogged down by the sheer volume of information. This collaborative dynamic would redefine the relationship between students and AI, transforming it from a tool to a cognitive partner.

AI in the Curriculum: A Necessity, Not an Option

Another crucial insight from the study is that 100% of students surveyed believe AI should be formally taught in the medical curriculum. This points to a shift in the educational paradigm—future physicians must not only understand medicine but also the AI tools that will increasingly shape its practice.

By incorporating AI into the foundational elements of medical education, schools can prepare students to utilize LLMs effectively and ethically, maximizing their potential in both learning and patient care. This isn’t just about technological proficiency; it’s about empowering future doctors to work synergistically with AI to enhance healthcare outcomes. As 65.7% of students already report some exposure to AI in medicine or research, this integration is more a matter of formalizing what's already happening organically.

AI as the Future of Medical Learning

This current study shows that the integration of LLMs into medical education is not just a trend—it’s a signal of the future. With students embracing LLMs for their versatility, accuracy, and ability to reduce cognitive strain, AI is reshaping what it means to learn and practice medicine. The implications are important: future doctors will work hand-in-hand with AI, using it to personalize their education, streamline their workload, and ultimately provide better patient care. As AI continues to evolve, medical education will need to keep pace, teaching not just medical knowledge but also how to best leverage these powerful tools.

By embracing LLMs now, medical students are laying the groundwork for a healthcare system where AI is not just an assistant, but a full-fledged collaborator in both education and practice. This transformation marks a new chapter in medicine, one where the art of healing is empowered by the science of AI.