Utilizing a Learning Strategy Analysis to Determine a System’s Potential Impact on Student Learning: The Augmented-Reality Emotive Virtual Patient System Platform

Abstract

A learning strategy analysis was performed on the Emotive Virtual Patient System, an augmented reality platform that teaches medical students doctor-patient communication skills. The Emotive Virtual Patient System is a complex mixed reality platform that includes both virtual and human peers/instructors who use natural language processing to provide feedback and dialog modeling as a means to improve patient communication learning outcomes. The learning strategy analysis (i.e., system learning strategy/component review, literature review, and heuristic evaluation of best practices) was conducted on the early system plans to determine its potential in supporting student learning and to provide shortand-long-term design considerations. The analysis identified three major categories for potential consideration: verbal interactions, user groups/system objective monitoring, and security. Specific recommendations were given for each of these areas, as supported by the literature.