Improving Cross-Disciplinary Knowledge Transfer for Bio-Inspired Engineering Design

Bio-inspired design has become a significant driver of innovation, enabling the development of effective solutions to some of the world's toughest challenges. Bio-inspired design leverages evolutionary advancements to create products and processes that are often more efficient and sustainable. However, applying biological insights to engineering can be challenging due to the distinct ways the two disciplines define and interpret core concepts. This paper explores the cognitive and technical skills required to effectively translate biological inspiration into engineering solutions. Our hypothesis focuses on bridging the "language and representation gap" between biology and engineering. The goal of this paper is to identify key aspects of biological representation that enable its successful adaptation into engineering design, fostering the development of more impactful and efficient bio-inspired solutions. The analysis of student feedback and ideation outputs revealed that engineers preferred biology texts with a medium level of technical complexity, balancing ease of understanding with image quantity. Basic references were found to support diverse idea generation, while more technical texts proved useful and necessary for understanding in-depth biological insights and applying them to engineering problems. Future research could explore the impact of information presentation order, the role of biological experts in deepening insights, and the use of machine learning to refine how biological information is selected and categorized to enhance the bio-inspired design process.