Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning
International Journal of Artificial Intelligence in Education, ISSN: 1560-4306, Vol: 26, Issue: 2, Page: 730-755
2016
- 68Citations
- 207Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
This paper argues that the research field of Artificial Intelligence in Education (AIED) can benefit from integrating recent technological advances (e.g.; wearable devices, big data processing, 3D modelling, 3D printing, ambient intelligence) and design methodologies, such as TORMES, when developing systems that address the psychomotor learning domain. In particular, the acquisition of motor skills could benefit from individualized instruction and support just as cognitive skills learning has over the last decades. To this point, procedural learning has been considered since the earliest days of AIED (dating back to the 1980's). However, AIED developments in motor skills learning have lagged significantly behind. As technology has evolved, and supported by the do-it-yourself and quantified-self movements, it is now possible to integrate emerging interactive technologies in order to provide personal awareness and reflection for behavioural change at low cost and with low intrusion. Many activities exist that would benefit from personalizing motor skills learning, such as playing a musical instrument, handwriting, drawing, training for surgery, improving the technique in sports and martial arts, learning sign language, dancing, etc. In this context, my suggestions for AIED research in the coming 25 years focus on addressing challenges regarding 1) modelling the psychomotor interaction, and 2) providing appropriate personalized psychomotor support.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84963622370&origin=inward; http://dx.doi.org/10.1007/s40593-016-0103-2; http://link.springer.com/10.1007/s40593-016-0103-2; http://link.springer.com/content/pdf/10.1007/s40593-016-0103-2; http://link.springer.com/content/pdf/10.1007/s40593-016-0103-2.pdf; http://link.springer.com/article/10.1007/s40593-016-0103-2/fulltext.html; https://dx.doi.org/10.1007/s40593-016-0103-2; https://link.springer.com/article/10.1007/s40593-016-0103-2
Springer Science and Business Media LLC
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