Emotions in Empathy Training Using Virtual Reality in Real-World Scenarios: An Interdisciplinary Framework

• In Event: Putting Tasks Under the Microscope: Task Features Triggering Emotions and Modulating Their Effects on Learning

Abstract

Objectives

Emotions are essential for learning, problem-solving, and reasoning across humans, tasks, domains, and contexts (Bohn-Gettler, 2019; Pekrun & Linnenbrink, 2014). A notable emotion-related process is empathy, which is critical for successful learning, problem solving, reasoning within high-stress, dynamic real-world scenarios across learning and workplace contexts (Wieck et al., 2021). Empathy is the capacity to understand or feel what another person is experiencing from within their frame of reference, that is, one’s ability to place themself in another's position to understand their cognitive, emotional, and physical experiences (Cuff et al., 2016). Effectively responding to high-stress, dynamic real-world scenarios (e.g., caring for critically-ill patients in emergency rooms, down-regulating high-school students’ negative emotions) involves emotions and is critically important for mitigating the detrimental effects these pose on learning, reasoning, and problem-solving. We argue that virtual reality (VR) environments are ideal research and training tools to examine and foster empathy in humans. Our paper outlines a theoretically- and empirically-based framework for using VR as a research and training tool to measure, understand, and foster empathy across humans in learning and workplace contexts with an emphasis on what, when, and how task features modulate the relationship between emotions and learning.

Theoretical Framework

Literature is replete with examinations of various aspects of empathy, including neurocognitive bases, aimed at isolating the cortical systems associated with cognitive, affective, and behavioral processes (Christov-Moore et al., 2020). Recent work on empathy has focused on empathy training (Wondra & Ellsworth, 2015). More recently and directly related to our paper, there has been increased attention to the use of VR to induce empathy and measure its impact across contexts (Yalcin & DiPaola, 2019). In our paper, we argue for the design of virtual environments to serve as research tools for inducing and testing empathy-related emotions and as training tools using embedded virtual humans to provide explicit empathy training (e.g., emotion regulation, McRae & Gross 2020; Zaki, 2020).

Methodological and Analytical Approach

Our presentation will focus on (1) synthesizing theoretical and empirical research on empathy with a focus on what, when, and how task features in VR environments modulate the relationship between emotions and learning; (2) describing methods for using multimodal multichannel process data (e.g., eye movements, verbalizations, physiology, video recordings of human-machine interactions; Azevedo et al., 2019) to identify, measure, and understand empathy related to various real-word scenarios; and (3) reporting on the design of embedded virtual humans capable of detecting, modeling, and fostering empathy in humans handling real-world scenarios.



Significance

Our proposed interdisciplinary framework is meant to extend the current understanding of empathy and how task features modulate the empathy-learning connection. We will consider the evidence for the underlying cognitive, affective, metacognitive, motivational, and social processes that unfold during real-life scenarios within VR-based empathy training systems. Such VR-based empathy training systems can provide humans across workforce sectors (e.g., teachers, clinicians, law enforcement officers) with individualized scaffolding and feedback based on their multimodal trace data, performance, and self-report measures.

Authors

• Roger Azevedo, University of Central Florida
  Presenting Author

• Vishav Jyoti, University of Central Florida
  Non-Presenting Author

• Ryan McMahan, University of Central Florida
  Non-Presenting Author