An experiment tested six generative large language models against students in an online introductory biomedical and health informatics course. The models scored higher than as many as three quarters of the real-world students in the class.
William Hersh, M.D., who has taught generations of medical and clinical informatics students at Oregon Health & Science University, found himself curious about the growing influence of artificial intelligence. He wondered how AI would perform in his own class.
As a professor of medical informatics and clinical epidemiology in the OHSU School of Medicine, Hersh is especially attuned to new technologies. The role of technology in education is nothing new, Hersh said, recalling his own experience as a high school student in the 1970s during the transition from slide rules to calculators."Clearly, everyone should have some kind of foundation of knowledge in their field," Hersh said.
The study is the first to compare large-language models to students for a full academic course in the biomedical field. Hersh and Fultz Hollis noted that a knowledge-based course such as this one may be especially ripe for generative, large-language models, in contrast to more participatory academic courses that help students develop more complex skills and abilities.
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