Skills are fundamental determinants of human task performance. Moreover, in industrial production, skills strongly relate to quality outcomes; therefore, this domain is a well suited testing environment for an investigation on skills.
This thesis reflects upon the existing body of theories and models around the topic. It provides clarification on the term, its associations, and expectations. Reviewing enabling factors, development and categorization possibilities of skills, the thesis proposes an integrated model composed of relevant features of established models with high relevancy to industrial production.
The thesis reviews physiological and organizational indicators capable of sensing skill-related concepts of the proposed integrated model in industrial production and proposes to use eye-hand coordination to sense work task performance?s cognitive and physical nature.
Consequently, the thesis investigates in three empirical studies conducted in one laboratory and two real-world settings, if the proposed eye-hand coordination measurement mechanism provides relevant insights into task performance, task-related (motor) skills, and the expertise of workers.
Finally, it provides relevant directions for future research and exploitation opportunities for the presented work, particularly user-adaptation strategies for cognitive systems.
Summarizing, the contributions of this thesis are, therefore, (i) a reference terminology, (ii) an integrated model for building skill-aware systems, (iii) a structured survey of skill-related indicators, and the establishment of eye-hand coordination as a worthwhile sensing technology for industrial production, (iv) a sensor fusion approach for measuring eye-hand coordination, empirical validation that eye-hand coordination can sense (v) task-related skill and (vi) expertise-related skill and (vii) a methodology to conduct skill experiments in combination with the proposed integrated model.