E-learners Kansei experience towards expert-like virtual agent: A case study

The rapid growth of Internet users and diverse Web 5.0 technologies has made the research scholars and educators to think of intelligent tools such as; expert-like virtual agents as an effective e-learning tool. The success of an e-learning tool relies primarily on the level of acceptance of the tool by the e-learners and their state of emotion while using the tool. Therefore, addressing e-learner's emotional competences is important to understand the implicit emotion of the young minds. In this context, virtual agents are expected to play the role of instructors in a virtual learning environment. This paper aims to study the affective design of the Virtual Agent in terms of attractiveness and realism that adopts Kansei Engineering, an emerging technology used to explore and validate the emotion structure defined as a complex state of feelings that can result in the changes of human behaviour and thoughts of e-learners. Adding on, the paper also highlights and validates the six universal emotions such as anger, happiness, surprise, disgust, sadness and fear. The findings suggest that the most attractive and realistic virtual agents have higher Kansei value. Some implications of the findings in relation to expert-like virtual agent design and Kansei are discussed in this paper.