Medical Student Experiential Learning in Telesimulation

Abstract

OBJECTIVES Telesimulation utilizes telecommunication technology to engage learners in simulation while in different physical locations. Despite this potential advantage, understanding of the student experience and assessment of student learning in telesimulation activities is limited. This study evaluates medical student emotional experience and self-identified learning in telesimulation through the Kolb experiential learning framework and qualitative analysis. METHODS Fourth-year medical students enrolled in the Spencer Fox Eccles School of Medicine at the University of Utah participated in 3 telesimulation activities as part of a required internal medicine course. Students were surveyed regarding their satisfaction with the activity (N = 114) and responded to questions about their emotional experience and self-identified areas of learning. Free-text responses were analyzed using qualitative content analysis to identify themes until thematic saturation (N = 66). RESULTS Students were highly satisfied with telesimulation, with greater than 90% of students expressing a positive view of simulation realism, debrief quality, and group size. Themes of anxiety and uncertainty, confidence versus incompetence, team dynamics, fun, and difficult patient interaction were identified regarding the emotional experience. Themes of communication and teamwork, managing emotions, information gathering, differential diagnosis, resource reference, executing treatment, and medical knowledge were identified regarding student-identified learning. CONCLUSION In this analysis of medical student experiences with telesimulation, we found students have rich emotional, cognitive, and behavioral experiences and self-identify learning across a variety of domains. Our findings support further study of telesimulation for medical student learning and demonstrate how assessment of outcomes via Kolb framework, using the learner's reflective observation and self-identified learning, may help better define learning outcomes from simulation.