Affective Learning: Empathetic Agents with Emotional Facial and Tone of Voice Expressions
Empathetic behavior has been suggested to be one effective way for Embodied Conversational Agents (ECAs) to provide feedback to learners' emotions. An issue that has been raised is the effective integration of parallel and reactive empathy. The aim of this study is to examine the impact of ECAs' emotional facial and tone of voice expressions combined with empathetic verbal behavior when displayed as feedback to students' fear, sad, and happy emotions in the context of a self-assessment test. Three identical female agents were used for this experiment: 1) an ECA performing parallel empathy combined with neutral emotional expressions, 2) an ECA performing parallel empathy displaying emotional expressions that were relevant to the emotional state of the student, and 3) an ECA performing parallel empathy by displaying relevant emotional expressions followed by emotional expressions of reactive empathy with the goal of altering the student's emotional state. Results indicate that an agent performing parallel empathy displaying emotional expressions relevant to the emotional state of the student may cause this emotion to persist. Moreover, the agent performing parallel and then reactive empathy appeared to be effective in altering an emotional state of fear to a neutral one.
empathy computers and education intelligent agents user interfaces