From May 16th to 17th, 2024, Hendrik Drachsler and Marcel Schmitz (TETRA AI, ZUYD University of Applied Science) had the pleasure of providing a FoLA workshop at the College of Anaesthesiologists of Ireland (CAI) in Dublin, Ireland, under the support of the Insight research centre. Together with members from CAI and from the ASSERT Centre, College of Medicine and Health, University College Cork (UCC), they used the FoLA tool to plan a simulation-based training for high-risk clinical situations using highly informative feedback. Data from these trainings will be collected and analyzed to determine how effective this training is in improving the performance of the attendees.

The study is being planned to take place with around 100 doctors in training at two simulation training centers: at ASSERT Centre UCC and at CAI. Participants will attend a one-day intensive simulation-based training course focused on emergency situations. These courses are part of standard intern training or a national anesthesiology program, with about 12 attendees each. Participants will engage in 4-6 simulated scenarios, where two actively participate while others observe, and a researcher records data on performance using validated evaluation systems.

Real-time data on learner physiology and movements may also be collected. Each scenario is followed by a structured debrief session. The course includes high-fidelity simulations, recorded interactions, and facilitated debriefs to enhance non-technical skills and communication. Data-enriched Learning Activities (DeLAs) will be designed to collect and analyze relevant data to improve learning outcomes.

The main goal is to evaluate the impact of providing simulation-based training for high-risk clinical situations using highly informative feedback. This feedback is generated from:

  • Initial information describing each student (including their ability to understand and use feedback),
  • Student engagement with data-enhanced educational activities and
  • Measured outcomes in a simulated environment.

The secondary goals are to:

  • Assess the practicality of creating and providing highly informative feedback using multiple data sources.
  • Gather student opinions on the usefulness and value of data-enriched feedback, particularly for high-risk clinical scenarios, considering its format, timing, and content.
  • Investigate potential links between students’ ability to understand and use feedback and both their performance improvements and their appreciation of highly informative feedback.
  • Develop new datasets that can be used to train and test AI tools for analyzing learning and performance factors.

The collected data will later be analyzed to determine its usefulness as a test or training dataset for future studies on categorizing and better understanding the relationships between learner characteristics, activity types and clinical performance.