Influencing the Learning Experience Through Affective Agent Feedback in a Real-World Treasure Hunt

Mary Ellen Foster, Amol Deshmukh, Srinivasan Janarthanam, Mei Yii Lim, Helen Hastie, Ruth Aylett

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We explore the effect of the behaviour of a virtual robot agent in the context of a real-world treasure-hunt activity earned out by children aged 11-12. We compare three conditions: a traditional paper-based treasure hunt, along with a virtual robot on a tablet which provides either neutral or affective feedback during the treasure hunt. The results of the study suggest that the use of the virtual robot increased the perceived difficulty of the instruction-following task, while the affective robot feedback in particular made the questions seem snore difficult to answer.
Original languageEnglish
Title of host publicationAAMAS '15: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
Place of PublicationUnited States
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems
Pages1711-1712
Number of pages2
Volume3
ISBN (Print)9781450337717
DOIs
Publication statusPublished - 4 May 2015
Event2015 International Conference on Autonomous Agents and Multiagent Systems - Istanbul, Turkey
Duration: 4 May 20158 May 2015

Conference

Conference2015 International Conference on Autonomous Agents and Multiagent Systems
Abbreviated titleAAMAS'15
Country/TerritoryTurkey
CityIstanbul
Period4/05/158/05/15

Keywords / Materials (for Non-textual outputs)

  • robotic tutors
  • empathy
  • human-robot interaction

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