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Understanding the role of Interactive Machine Learning in Movement Interaction Design

Gillies, Marco. 2019. Understanding the role of Interactive Machine Learning in Movement Interaction Design. ACM Transactions on Computer-Human Interaction, 26(1), ISSN 1073-0516 [Article]

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Abstract or Description

Interaction based on human movement has the potential to become an important new paradigm of human computer interaction, but for it to become mainstream there need to be effective tools and techniques to support designers. A promising approach to movement interaction design is Interactive Machine Learning, in which designing is done by physically performing . This paper brings together many different perspectives on understand human movement knowledge and movement interaction. This understanding shows that the embodied knowledge involved in movement interaction is very different from the representational knowledge involved in a traditional interface so a very different approach to design is needed. We apply this knowledge to understanding why interactive machine learning is an effective tool for motion interaction designers and to make a number of suggestions for future development of the technique

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1145/3287307

Additional Information:

"© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Computer-Human Interaction, {VOL 26, ISS 1, (2019)} http://doi.acm.org/10.1145/3287307"

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
22 October 2018Accepted
23 February 2019Published

Item ID:

24757

Date Deposited:

24 Oct 2018 11:35

Last Modified:

28 Jun 2019 06:03

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

http://research.gold.ac.uk/id/eprint/24757

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