Intelligent systems for psychomotor learning: a systematic review and two cases of study
Alberto Casas-Ortiz, Jon Echeverría, Olga C. Santos
Abstract
This chapter reviews the state-of-the-art of AIED systems for psychomotor learning, which are systems that support the learning of motor skills in a personalized way, especially regarding complex motor skills such as playing a musical instrument, performing surgery tasks, or practicing sports and martial arts. A systematic review is carried out in the chapter. A total of 12 papers are analyzed in terms of the AI (Artificial Intelligence) support and the ED (educational) objective involved. After that, the motion information flow in those systems to manage the personalization is reviewed following four phases: sensing motion, modeling motion, designing feedback, and delivering feedback. Subsequently, we present two martial arts systems, KSAS and KUMITRON, as cases for study. We expect that the contents of this chapter will provide some background for teachers, researchers, and PhD students with respect to the state-of-the-art AIED psychomotor systems and how to deploy the required processing steps to build AIED psychomotor systems.