EAGER: AnalyzeD - Analyzing Engineering Design Activities

Stanford University, Stanford CA

Investigators

Abstract

The research objective of this EArly concept Grant for Exploratory Research (EAGER) award is to quantitatively measure, model, and understand the relationships between engineering design behavior (actual engineering activity), problem solving preference (individual psychological predisposition), and real-time physiological responses of engineers (EEG, ECG, and other physiology telemetry data). It will result in an engineering design measurement system that will help improve decision analysis models by reducing individual behavior-based uncertainty, as well as data that will support the formation and optimization of design teams, enabling new insights into the interactions between engineering designers and their contextual environments (e.g., computational and collaborative tools, spaces, and machines). This research will facilitate the integration of analytical creativity and structured engineering approaches with the less structured creativity of divergent rapid prototyping to enable design teams and technical organizations to increase the level of transformation, speed, and value of their product/system development and design processes. If successful, the results of this research will provide insight into the underlying cognitive processes taking place as engineering designers make decisions (alone and in teams), including the relationship between the amount of stress experienced under different amounts of uncertainty based on the type of design activity and the problem solving preference of the individuals. The results will enable the development of new supportive tools and environments to assist in the resolution of complex engineering challenges, while taking the individual psychological predispositions of the engineers and the specific divergent or convergent nature of the design activity into account. This knowledge will enable the facilitation of mental pivoting between the divergent and convergent engineering design phases, as well as the maximization of each individual engineer's participation and output in both phases.