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Identifying task engagement: Towards personalised interactions with educational robots
KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).ORCID iD: 0000-0002-7257-0761
2013 (English)In: Proceedings - 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013, 2013, 655-658 p.Conference paper, Published paper (Refereed)
Abstract [en]

The focus of this project is to design, develop and evaluate a new computational model for automatically detecting change in task engagement. This work will be applied to robotic tutors to enhance and support the learning experience, enabling timely pedagogical and empathic intervention. This work is intended to forward the current state of the art by 1) exploring how to automatically detect engagement with a learning task, 2) designing and developing new approaches to machine learning for adaptive platform-independent modelling and 3) evaluation of its effectiveness for building and maintaining learner engagement across different tutor embodiments, for example a physical and virtual embodiment.

Place, publisher, year, edition, pages
2013. 655-658 p.
Keyword [en]
Engagement, Human-robot interaction, Robotic tutors, Social robots
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:kth:diva-143597DOI: 10.1109/ACII.2013.114ISI: 000333833400108Scopus ID: 2-s2.0-84893284817ISBN: 978-076955048-0 (print)OAI: oai:DiVA.org:kth-143597DiVA: diva2:707896
Conference
2013 5th Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013; Geneva; Switzerland; 2 September 2013 through 5 September 2013
Note

QC 20140326

Available from: 2014-03-26 Created: 2014-03-25 Last updated: 2014-03-26Bibliographically approved

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Peters, Christopher

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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