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'...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/62508d8add3e4df7b5b36cb861655ea8 |
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| Sumario: | <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. |
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