What part can Natural Language Processing (NLP) and machine learning play in the advancement of medical education assessment?

Read some of the highlights from recent articles published by NBME researchers as they continue to explore the use of NLP in transforming assessment development and scoring.

Though NLP traces its roots back only to the 1960s, the field has seen significant advances in recent years. NLP has tremendous transformative potential in medical education assessment development and scoring, especially in more complex areas that pose unique measurement challenges.

NBME is committed to fostering innovation to ensure that medical education assessment practices continue to evolve. To that end, we are researching the use of NLP in improving the assessment of clinical reasoning skills, constructing new scoring systems, and more.

This research summary explores the highlights of some of this recent research and discusses their progress in utilizing NLP to advance medical education assessment.

For more reading on NLP and other topics, visit the NBME Research Library. You can also learn more about the use of NLP in medical education assessment and the wider field of medicine in a short video featuring Victoria Yaneva, Manager, Data Science at NBME.

Medical education needs to support the advancement of skills and behaviors alongside knowledge, so students can develop as complete physicians, ready to take on patient care. We’re rethinking measurement to facilitate this evolution, but we can’t do it without new perspectives and ideas.