Publication:

Learning How to Write with a Social Robot

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CHILI

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Dillenbourg, Pierre

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datacite.rights

openaccess

dc.contributor.advisor

Dillenbourg, Pierre

dc.contributor.advisor

Paiva, Ana

dc.contributor.author

Chandra, Shruti

dc.date.accepted

2019

dc.date.accessioned

2019-05-01T14:46:19

dc.date.available

2019-05-01T14:46:19

dc.date.created

2019-05-01

dc.date.issued

2019

dc.date.modified

2025-02-19T14:33:26.983355Z

dc.description.abstract

Learning handwriting is one of the main occupations for children in primary education. It is a complex skill that has been associated with children’s learning and development. Poor handwriting skills affect children negatively concerning their academic performance and motivation. In schools, children with handwriting problems need extra support and one-to-one interventions from teachers. Personalised one-to-one support requires additional resources that most schools generally cannot afford. Therefore, there is a need to explore different methods of learning and contemporary technologies to develop new educational tools to foster children’s learning process of handwriting. The research presented in this thesis addresses the question of - “How to create a social robot that can help children to acquire handwriting skills?". Thus, we looked into three different research domains: education; pedagogic sciences; and social human-robot interaction (HRI). On the one hand, we investigated the types of errors commonly present in children’s handwriting. On the other hand, we needed to explore different educational theories to find alternate learning methods that would maximise children’s learning gains. In addition, we investigated various possibilities for integrating a social robot into educational scenarios and measured its impact on the children’s learning process. This thesis presents five studies that follow an incremental evolution of the research. The first three studies were based on the interaction between two children, in the presence of either a human or a robotic facilitator, with the children performing a collaborative writing activity. We explored the ‘peer-learning’ and ‘peer-tutoring’ methods and compared the differences in terms of interaction behaviour and learning gains. Further, we analysed children’s interpersonal distance and feelings of responsibility towards their peers, both in the presence of a robot and human facilitator. Finally, we examined children’s assessment behaviour towards their peers and self-disclosure towards the robotic facilitator. The outcomes of these first studies provided enough data to generate a taxonomy of children handwriting errors to be used in the subsequent studies. They hinted that the ‘peer-tutoring’ method had a positive influence on children’s learning and corrective feedback to their peers in the presence of the social robot, providing positive support to the applicability of social robots as ‘facilitators’ in handwriting learning. The next step was to study the effects of the robot in the peer-tutoring scenario when assuming the role of a peer, directly interacting and performing a collaborative writing activity with the children. Thus, we developed an educational system with an autonomous social behaviour of a robot exhibiting various levels of learning competencies. The tutor-child provides corrective feedback on the writing of the learner-robot and in turn, enhances his writing skills. The robot’s writing was generated by an algorithm incorporating human-inspired movements and could reproduce a set of writing errors from the error taxonomy. We tested the system by conducting two longitudinal studies, each of them composed of four sessions. In the fourth study, we assigned the robot two contrasting competencies: ‘learning’ and ‘non-learning’. We measured the differences in children’s learning gains and changes in their perceptions towards the learner-robot. The fifth study followed a similar interaction scenario and research questions, but this time the robot performed three learning competencies: ‘continuous-learning’;’non-learning’ and ‘personalised-learning’. The findings of these studies show that the children improved more with the robot exhibiting learning, continuous-learning and personalised-learning competencies compared to the robot showing non-learning competency. The way children’s learning and perception of the robot evolved over time confirmed the need for multiple sessions for the last two studies. This thesis presents some evidence that social robots can be successfully used as tools for enhancing children’s handwriting skills in peer-learning scenarios.

dc.description.notes

Co-supervision with Instituto Superior Técnico (IST) da Universidade de Lisboa, Doutoramento em Engenharia Electrotécnica e de Computadores

dc.description.sponsorship

CHILI

dc.identifier.doi

10.5075/epfl-thesis-9244

dc.identifier.uri

https://infoscience.epfl.ch/handle/20.500.14299/156223

dc.language.iso

en

dc.publisher

EPFL

dc.publisher.place

Lausanne

dc.relation

https://infoscience.epfl.ch/record/265505/files/EPFL_TH9244.pdf

dc.size

300

dc.subject

handwriting

dc.subject

child-robotinteraction

dc.subject

peer-basedlearning

dc.subject

autonomousrobot

dc.subject

collaborative learning

dc.title

Learning How to Write with a Social Robot

dc.type

thesis::doctoral thesis

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Publication

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oai:infoscience.epfl.ch:265505

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Theses

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THESIS

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fulltext

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DOI

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thesis-public

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thesis

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OpenAIREv4

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IC

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http://purl.org/coar/version/c_970fb48d4fbd8a85

epfl.thesis.doctoralSchool

EDRS

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IC

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IINFCOM

epfl.thesis.jury

Prof. Alcherio Martinoli (président) ; Prof. Pierre Dillenbourg, Prof. Ana Paiva (directeurs) ; Dr Isabel Maria Martins Trancoso, Dr Tony Belpaeme, Dr Sandra Y. Okita (rapporteurs)

epfl.thesis.number

9244

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CHILI

epfl.thesis.publicDefenseYear

2019-02-01

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EPFL

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