Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site.... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.

menu

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.