BACKGROUND
Social skills training by human trainers is a well-established method to obtain appropriate social interaction skills and strengthen social self-efficacy. Our previous works automated social skills training by developing a virtual agent that teaches social skills through interaction. This study attempts to investigate the effect of virtual agent design on automated social skills training. However previous works have not investigated virtual agent design for virtual social skills trainers.
OBJECTIVE
The three main purposes of this research are summarized: to investigate virtual agent appearance for automated SST, to investigate the relationship between acceptability and other measures (likeability, acceptability, realism, and familiarity), and to investigate the relationship between likeability and an individual’s characteristics (gender, age, and autistic traits).
METHODS
We prepared images and videos of a virtual agent, and 1,218 crowdsourced workers rated the virtual agents through a questionnaire. In designing personalized virtual agents, we investigated the acceptability, likeability, and other impressions of the virtual agents and their relationship to the individuals’ characteristics.
RESULTS
As a result, we found the difference between the virtual agents in all measures (P < 0.001). A female anime-type virtual agent was rated as the most likeable. We also confirmed that participants’ gender, age, and autistic traits are related to the ratings.
CONCLUSIONS
We confirmed the effect of virtual agent design on automated social skills training. Our findings are important in designing the appearance of an agent for use in personalized automated social skills training.
