Towards Personalised Learning of Psychomotor Skills with Data Mining

Data Mining (DM) currently represents a key element for improving the acquisition of knowledge and for providing proper feedback in educational environments. In this field, as well as in others, psychomotor skills represent a unique way to advance in the knowledge of human behaviours. Our research apply in two equally promising, but different domains. On one hand, we would be able to improve the learning of psychomotor skills at educational level with the use of different DM techniques. This may includes learning martial arts or supporting the acquisition of locomotor abilities. On the other hand, we would like to expand our DM research far beyond the basis of the aforementioned educational field. Thus, we can evaluate other users, such patients, with the aim of improving the re-learning of motor capabilities during recovery processes on rehabilitation, or even to detect cognitive impairments, analysing slight psychomotor alterations at early stages using DM. The latter includes gait analysis, which are currently used for screening, but not so much for predicting purposes. Although our research is still at early stages, we are following the principles set on previous researches, such those included in our intelligent Expertise Level Assessment (iELA) method.