• DocumentCode
    2085755
  • Title

    Toys++ AR Embodied Agents as Tools to Learn by Building

  • Author

    Simeone, Luca ; Iaconesi, Salvatore

  • Author_Institution
    FakePress, Univ. La Sapienza, Rome, Italy
  • fYear
    2010
  • fDate
    5-7 July 2010
  • Firstpage
    649
  • Lastpage
    650
  • Abstract
    This paper presents a prototype for an augmented-reality based toy. Toys++ is grounded on the concept that the actual activity of building tangible artifacts can speed up learning processes. Toys ++ aims at assembling a framework that will allow the use of existing physical components of the toy as triggers. When the toy is placed under the webcam, a pre-trained 3D feature recognition system scans the entire figure, trying to identify some specific components. If any of these elements are recognized, the system will retrieve and show educational content from selected sources (texts, videos, pictures).
  • Keywords
    augmented reality; computer aided instruction; feature extraction; software agents; AR embodied agent; Toys++; educational content retrieval; figure scanning; learning tool; pretrained 3D feature recognition system; Artificial intelligence; Conferences; augmented reality; component; constructionism; enhanced learning; mathetics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies (ICALT), 2010 IEEE 10th International Conference on
  • Conference_Location
    Sousse
  • Print_ISBN
    978-1-4244-7144-7
  • Type

    conf

  • DOI
    10.1109/ICALT.2010.184
  • Filename
    5572598