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:	Hiroki Tanaka, Hidemi Iwasaka, Yasuhiro Matsuda, Kosuke Okazaki, Satoshi Nakamura
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Embodied conversational agents self-efficacy social skills training summary feedback Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/62508d8add3e4df7b5b36cb861655ea8
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spelling	oai:doaj.org-article:62508d8add3e4df7b5b36cb861655ea82021-11-24T00:03:58ZAnalyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training2644-127610.1109/OJEMB.2021.3075567https://doaj.org/article/62508d8add3e4df7b5b36cb861655ea82021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9416779/https://doaj.org/toc/2644-1276<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.Hiroki TanakaHidemi IwasakaYasuhiro MatsudaKosuke OkazakiSatoshi NakamuraIEEEarticleEmbodied conversational agentsself-efficacysocial skills trainingsummary feedbackComputer applications to medicine. Medical informaticsR858-859.7Medical technologyR855-855.5ENIEEE Open Journal of Engineering in Medicine and Biology, Vol 2, Pp 65-70 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Embodied conversational agents self-efficacy social skills training summary feedback Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5
spellingShingle	Embodied conversational agents self-efficacy social skills training summary feedback Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5 Hiroki Tanaka Hidemi Iwasaka Yasuhiro Matsuda Kosuke Okazaki Satoshi Nakamura Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
description	<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.
format	article
author	Hiroki Tanaka Hidemi Iwasaka Yasuhiro Matsuda Kosuke Okazaki Satoshi Nakamura
author_facet	Hiroki Tanaka Hidemi Iwasaka Yasuhiro Matsuda Kosuke Okazaki Satoshi Nakamura
author_sort	Hiroki Tanaka
title	Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
title_short	Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
title_full	Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
title_fullStr	Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
title_full_unstemmed	Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training
title_sort	analyzing self-efficacy and summary feedback in automated social skills training
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/62508d8add3e4df7b5b36cb861655ea8
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Analyzing Self-Efficacy and Summary Feedback in Automated Social Skills Training

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