Using facial expressiveness of a virtual agent to induce empathy in users

Abstract

Healthcare simulators are learning environments that offer many training opportunities. The integration of expressive virtual patients in these simulators encourages the exchanges and provokes emotional reactions in the learner, which promotes memorization and learning. Based on these elements, we assume that the facial expressiveness of a virtual agent is a factor to be considered in order to improve the user experience. We investigate the impact of the facial expressiveness of virtual humans on the empathy induction in the user of health simulators. We also investigate the impact of facial expressiveness on the user’s sense of similarity and the affective bond with the agent. Our results show a high empathy score when users train with simulators. Depending on the context, we observe a significant difference in perspective-taking in favor of the users who interact with an expressive virtual agent to a virtual agent without facial expressiveness.