Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning

• Published in: International journal of artificial intelligence in education Vol. 26; no. 2; pp. 730 - 755
• Main Author: Santos, Olga C.
• Format: Journal Article
• Language: English
• Published: New York Springer New York 01-06-2016; Springer; Springer Nature B.V
• Subjects: Ambient intelligence; Artificial Intelligence; Cognition & reasoning; Cognitive ability; Computer Science; Computers and Education; Customization; Data Analysis; Data processing; Educational Environment; Educational Technology; Handwriting; Human Body; Individualized Instruction; Learning; Learning Processes; Learning Strategies; Memory; Metacognition; Modelling; Motor ability; Musical instruments; Psychomotor performance; Psychomotor Skills; Skill Development; Skills; Teaching Methods; Technology Integration; Technology Uses in Education; Thinking Skills; Three dimensional models; Three dimensional printing; Training; User Interfaces and Human Computer Interaction; Wearable technology; Motor skills learning; Ambient intelligence; Wearable devices; TORMES methodology; Internet of me; 3D modelling; Education; Big data; Psychomotor learning domain; Procedural learning; Artificial intelligence; 3D printing; Quantified-self
• ISSN: 1560-4292; 1560-4306
• DOI: 10.1007/s40593-016-0103-2

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.