Teaching medicine web-based with the help of interactive audience response systems

PLoS One. 2023 Aug 15;18(8):e0289417. doi: 10.1371/journal.pone.0289417. eCollection 2023.

Abstract

The COVID-19 pandemic confronted the medical community worldwide with numerous challenges, not only with respect to medical care, but also for teaching the next generation of physicians. To minimize the risk of infections patient-unrelated classes can be held digitally. Here we present a student initiated, web-based teaching approach, called "From symptom to diagnosis". In this seminar case reports of rare diseases were presented to the audience in a symptom-focused manner. The patients´ most significant symptoms were presented, followed by an in-depth discussion about differential diagnosis. First glance diagnosis pictures were shown to improve students´ ability to identify important clinical scenarios. We used chat functions as well as an audience response system to make the seminar more interactive. By this we attracted between 71 and 147 participants per session. The online seminar was very well perceived and 97% of the students saw an improvement of their diagnostic skills. In summary, we successfully established an interactive, web-based teaching format for medical students.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / diagnosis
  • Humans
  • Internet
  • Medicine*
  • Pandemics
  • Students, Medical*
  • Teaching

Grants and funding

This work was financially supported by Philipps-Universitat Marburg Fachbereich Medizin in the form of a Lehre@Philipp 2021 award (https://www.uni-marburg.de/de/universitaet/lehre/lehrprofil/lehrpreis/tag-der-lehre-2021) to PK & LR. This award supports the original costs for teaching projects and was less than 5.000,00 € for new IT-equipment and software tools (i.e. Pool Everywhere). This work was also financially supported by Dr. Reinfried Pohl Foundation (Marburg, Germany) in the form of an award to JRS. The funders had no additional role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.