Leveraging large language models to construct feedback from medical multiple-choice Questions.

ABSTRACT: Exams like the formative Progress Test Medizin can enhance their effectiveness by offering feedback beyond numerical scores. Content-based feedback, which encompasses relevant information from exam questions, can be valuable for students by offering them insight into their performance on the current exam, as well as serving as study aids and tools for revision. Our goal was to utilize Large Language Models (LLMs) in preparing content-based feedback for the Progress Test Medizin and evaluate their effectiveness in this task. We utilize two popular LLMs and conduct a comparative assessment by performing textual similarity on the generated outputs. Furthermore, we study via a survey how medical practitioners and medical educators assess the capabilities of LLMs and perceive the usage of LLMs

SUBMITTER: Tomova M 

PROVIDER: S-EPMC11561272 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature