Co-Occurrence of Self-Regulated Learning and Emotions: A Case Study on Learning to Manage Deteriorating Patients

• In Event: Simulation and Its Effects in Professions Education

Abstract

This case study examined medical students’ ability to stabilize deteriorating patients during a role-playing simulation. Differences between high and low performing students were noted in their ability to use a medical algorithm for managing such emergencies. Furthermore, performance differences were examined in relationship to medical students' self-regulated learning (SRL) activities and how such activities interact with their emotions during problem-solving. Student dialogues were captured during the Deteriorating Patient Activity (DPA) from 8 fourth year medical students and coded for SRL, epistemic emotions, and problem-solving behaviors. Sequential mining technique was used to analyze the data. Results showed that students with different level of knowledge followed the medical algorithm distinctively. They experienced different emotions and used distinct problem-solving behaviors during SRL activities.

Authors

• Chengyi Tan, McGill University
  Presenting Author

• Xiaoshan Huang, McGill University
  Non-Presenting Author

• Alejandra Ruiz-Segura, McGill University
  Non-Presenting Author

• Susanne P. Lajoie, McGill University
  Non-Presenting Author

• Jeffrey Wiseman, McGill University
  Non-Presenting Author