A multimodal approach for fostering knowledge transfer in engineering design activity: an eye-tracking and fNIRS study

Knowledge transfer in engineering design activity involves effectively applying prior practical experience in novel contexts. While related works fostering knowledge transfer focus on educational practices and experience generalisation, recent advancements enable us to analyze its complex cognitive processes using neuroimaging technology. This paper proposes a multimodal approach for facilitating knowledge transfer in engineering design, utilising functional near-infrared spectroscopy (fNIRS) and eye-tracking technologies based on neurocognitive profiling. We conducted knowledge transfer experiments using mixed and extended design tasks. Meanwhile, The analysis focused on gaze duration, gaze counts, brain region activation levels, functional connectivity, and effective connectivity of the participants. Finally, we employed stepwise linear regression to identify significant and potential associated factors of knowledge transfer. By combining eye-tracking predictors and brain network predictors, a multivariate linear discriminant analysis (LDA) significantly differentiated between participants in near-transferred and far-transferred states, achieving an accuracy of 91.16% using leave-one-out cross-validation. The 'basic-supplementary-target task' method effectively improved the knowledge transfer performance by 27.6%. Our findings demonstrate the efficacy of the proposed multimodal approach in facilitating knowledge transfer in engineering design activities.