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Goldsmiths - University of London

Using Machine Learning to Support Pedagogy in the Arts

Fiebrink, Rebecca. 2012. Using Machine Learning to Support Pedagogy in the Arts. Personal and Ubiquitous Computing, n/a, n/a-n/a. ISSN 1617-4909 [Article]

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Abstract or Description

Teaching artistic skills to children presents a unique challenge: High-level creative and social elements of an artistic discipline are often the most engaging and the most likely to sustain student enthusiasm, but these skills rely on low-level sensorimotor capabilities, and in some cases rote knowledge, which are often tedious to develop. We hypothesize that computer-based learning can play a critical role in connecting “bottom-up” (sensorimotor-first) learning in the arts to “top-down” (creativity-first) learning, by employing machine learning and artificial intelligence techniques that can play the role of the sensorimotor expert. This approach allows learners to experience components of higher-level creativity and social interaction even before developing the prerequisite sensorimotor skills or academic knowledge.

Item Type: Article

Identification Number (DOI):

10.1007/s00779-012-0526-1

Departments, Centres and Research Units:

Computing
Computing > Embodied AudioVisual Interaction Group (EAVI)
Research Office > REF2014

Dates:

DateEvent
2012Published

Item ID:

9425

Date Deposited:

04 Nov 2013 11:09

Last Modified:

20 Jun 2017 10:07

URI: http://research.gold.ac.uk/id/eprint/9425
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