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Interaction and reflection via 3D path shape qualities in a mediated constructive learning environment
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International Multimedia Conference archive
Proceedings of the international workshop on Educational multimedia and multimedia education table of contents
Augsburg, Bavaria, Germany
SESSION: Session 2 table of contents
Pages: 37 - 46  
Year of Publication: 2007
ISBN:978-1-59593-783-4
Authors
Kai Tu  Arizona State University
Harvey Thornburg  Arizona State University
Ellen Campana  Arizona State University
David Birchfield  Arizona State University
Matthew Fulmer  Arizona State University
Andreas Spanias  Arizona State University
Sponsors
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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ABSTRACT

The mixed-reality environment, or hybrid physical-digital space, is an emerging human-computer interaction paradigm with great potential to support constructive learning in everyday settings as a complement to traditional classroom methods. Key advantages over screen-based media and immersive (virtual-reality) environments include a) dynamic, multimodal feedback, which engages diverse learning styles through multiple modes of representation; b) affordance of unencumbered, full-body movement, which enables interactions to be physically embodied; and c) physical continuity with the classroom, which fosters informal collaborative and social interactions. For this potential to be realized, however, we must address significant challenges in interaction design. We must develop modes of interaction which are implicitly learnable, which afford full-body movement, and which are cognitively well adapted to large physical spaces. Furthermore, we must create a mechanism by which students can reflect on what they have "constructed" through interacting with the space, so that implicit learning can be leveraged in the interest of explicit understanding. To these ends, we have developed a novel interaction paradigm based around 3D path shape qualities: straight, curved, random, and stop, which describe motion of an illuminated object (glowball) guided by the participant through the space. We infer these qualities in real-time (online) and also offline using a robust Bayesian framework operating on a low-cost, non-intrusive video sensing apparatus. Online inference drives the interaction and offline segmentation the post-interaction display, our mechanism for reflection where segmentation results are mapped onto a physical trace of the participant.s motion. An informal study a) validates the implicit learnability of straight, curved, and stop mappings based on shape quality controls, and b) highlights the comparative advantage of the postinteraction display for all mappings, when subjects are asked to identify the actions responsible for specific target outcomes.


REFERENCES

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Collaborative Colleagues:
Kai Tu: colleagues
Harvey Thornburg: colleagues
Ellen Campana: colleagues
David Birchfield: colleagues
Matthew Fulmer: colleagues
Andreas Spanias: colleagues