Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
<italic>Goal:</italic> 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'...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Open Journal of Engineering in Medicine and Biology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9416779/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | <italic>Goal:</italic> 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. <italic>Methods:</italic> 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. <italic>Results:</italic> 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. <italic>Conclusions:</italic> Our system effectively summarized user feedback in terms of user self-efficacy and third-party ratings. |
|---|---|
| ISSN: | 2644-1276 |