Automatic analysis of summary statements in virtual patients - a pilot study evaluating a machine learning approach.

ABSTRACT:

Background

The ability to compose a concise summary statement about a patient is a good indicator for the clinical reasoning abilities of healthcare students. To assess such summary statements manually a rubric based on five categories - use of semantic qualifiers, narrowing, transformation, accuracy, and global rating has been published. Our aim was to explore whether computer-based methods can be applied to automatically assess summary statements composed by learners in virtual patient scenarios based on the available rubric in real-time to serve as a basis for immediate feedback to learners.

Methods

We randomly selected 125 summary statements in German and English composed by learners in five different virtual patient scenarios. Then we manually rated these statements bas

SUBMITTER: Hege I 

PROVIDER: S-EPMC7565765 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature