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Understanding Rapport over Multiple Sessions with a Social, Teachable Robot
Social robots have been shown to be effective educational tools. Rapport, or interpersonal closeness, can lead to better human-robot interactions and positive learning outcomes. Prior research has investigated the effects of social robots on student rapport and learning in a single session, but litt...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334666/ http://dx.doi.org/10.1007/978-3-030-52240-7_58 |
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author | Tian, Xiaoyi Lubold, Nichola Friedman, Leah Walker, Erin |
author_facet | Tian, Xiaoyi Lubold, Nichola Friedman, Leah Walker, Erin |
author_sort | Tian, Xiaoyi |
collection | PubMed |
description | Social robots have been shown to be effective educational tools. Rapport, or interpersonal closeness, can lead to better human-robot interactions and positive learning outcomes. Prior research has investigated the effects of social robots on student rapport and learning in a single session, but little is known about how individuals build rapport with a robot over multiple sessions. We reported on a case study in which 7 middle school students explained mathematics concepts to an intelligent teachable robot named Emma for five sessions. We modeled learners’ rapport-building linguistic strategies to understand whether the ways middle school students build rapport with the robot over time follow the same trends as human conversation, and how individual differences might mediate the rapport between human and robot. |
format | Online Article Text |
id | pubmed-7334666 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73346662020-07-06 Understanding Rapport over Multiple Sessions with a Social, Teachable Robot Tian, Xiaoyi Lubold, Nichola Friedman, Leah Walker, Erin Artificial Intelligence in Education Article Social robots have been shown to be effective educational tools. Rapport, or interpersonal closeness, can lead to better human-robot interactions and positive learning outcomes. Prior research has investigated the effects of social robots on student rapport and learning in a single session, but little is known about how individuals build rapport with a robot over multiple sessions. We reported on a case study in which 7 middle school students explained mathematics concepts to an intelligent teachable robot named Emma for five sessions. We modeled learners’ rapport-building linguistic strategies to understand whether the ways middle school students build rapport with the robot over time follow the same trends as human conversation, and how individual differences might mediate the rapport between human and robot. 2020-06-10 /pmc/articles/PMC7334666/ http://dx.doi.org/10.1007/978-3-030-52240-7_58 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Tian, Xiaoyi Lubold, Nichola Friedman, Leah Walker, Erin Understanding Rapport over Multiple Sessions with a Social, Teachable Robot |
title | Understanding Rapport over Multiple Sessions with a Social, Teachable Robot |
title_full | Understanding Rapport over Multiple Sessions with a Social, Teachable Robot |
title_fullStr | Understanding Rapport over Multiple Sessions with a Social, Teachable Robot |
title_full_unstemmed | Understanding Rapport over Multiple Sessions with a Social, Teachable Robot |
title_short | Understanding Rapport over Multiple Sessions with a Social, Teachable Robot |
title_sort | understanding rapport over multiple sessions with a social, teachable robot |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334666/ http://dx.doi.org/10.1007/978-3-030-52240-7_58 |
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