Cognitive factors of the transfer of empirical engineering knowledge: A behavioral and fNIRS study. (January 2021) - Wang, Fuhua; Jiang, Zuhua; Li, Xinyu; Li, Geng
Highlights: Empirical engineering knowledge is to solve specific problems in long-term practice. The neuroscience basis of empirical knowledge transfer is explored by fNIRS. A concept-sorting test inspired by the modified WCST is proposed. The individual cognitive structure is transferred under technological paradigm shifts. The distance of knowledge transfer is correlated to the performance and cognitive load. Abstract: Knowledge transfer is a progressive method to accelerate knowledge accumulation and technological innovation of enterprises. This hot research topic remains explorative on improving knowledge transfer efficiency in employees' training and engineering practice. However, due to ambiguous cognitive structure, how concepts and knowledge are stored and utilized in employees' minds during problem-solving was poorly answered. Therefore, this paper proposed a concept-sorting test, inspired by the modified Wisconsin Card-Sorting Test (M-WCST), to investigate the near/far transfer mechanism of empirical engineering knowledge (EEK) under the technological paradigm shift. Concept classification experiments were carried out for 31 participants by functional near-infrared spectroscopy (fNIRS) to explore the neuroscience basis of EEK transfer. Transfer performance and cognitive load measured in concept-sorting tests showed: (1) The cognitive level of the prior technological paradigm positively increases the transfer performance. However, it causes more perseverative errors due to set patterns of thinking. (2) The transfer distance negatively decreases the performance. Hence the display materials which are different from the prior cognitive structure are not beneficial for participants to learn. (3) The transfer distance significantly impacts the cognitive load. The activation level of brain areas becomes higher when people finish the near EEK transfer and apply it to solve new problems. As an explorative study, the evidence from fNIRS can provide insights into the theory and practice of empirical knowledge management.