Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training.

ABSTRACT

Goal Although automated social skills training has been proposed to enhance human social skills, the following two aspects have not been adequately explored what types of feedback are effective from virtual agents and the extent to which such systems enhance users' social self-efficacy. Methods: We developed an automated social skills trainer+ that follows human-based social skills training processes and implemented two types of feedback 1) a summary of the displayed feedback and 2) feedback based on the results of their previous training. Using our developed system, we measured social self-efficacy, feedback evaluations, and the third-party ratings of participants between pre- and post-training as well as their social responsiveness scales. Results: Self-efficacy is significantly correlated to the social responsiveness scale (r = -0.72) and can be improved with our system (mean improvement of 0.68, p < 0.05). The participants highly rated the feedback that was compared to their past training (14 out of 16, p < 0.05) more than the cases without it and the displayed summary feedback (11 out of 16, p = 0.21) more than the verbal comments. Conclusions: Our system effectively summarized user feedback in terms of user self-efficacy and third-party ratings.