Exploring the Impact of Cognitive Style and Academic Discipline on Design Prototype Variability

This paper describes a pilot study in which we explored the impact of cognitive style and academic discipline on the variability of prototypes in design tasks as part of a larger research project aimed at understanding the relationships between design behavior, cognitive preferences, and physiological reactions. Engineering and non-engineering students were asked to complete a simple design, build, and test task using an egg-drop design challenge. The students’ cognitive styles were assessed using the Kirton Adaption-Innovation Inventory (KAI); analysis revealed only slight differences between the engineering and non-engineering students in terms of cognitive style. Within-person comparisons of the similarity among built prototypes and the similarity between drawn and built prototypes were completed for each student; these results were correlated with discipline (engineering vs. non-engineering) and cognitive style to gain insight into their impact on students’ design choices. Results of these analyses are discussed here, along with implications and limitations of this pilot study and our plans for future work in this domain. 1. Research Context and Motivation This research is part of an NSF-funded collaborative project between Stanford University and Penn State University that spans the boundaries between engineering design and cognitive science (see Figure 1). Our extended aim is to understand and model the relationships between engineering design behavior (actual engineering design activity), cognitive preferences (individual psychological predisposition), and real-time physiological responses (EEG, ECG, heart rate, etc.) during design. Our research focuses primarily on the early stages of product and engineering system design and development, with potential for expansion across the entire design process. Figure 1. Key components of our research framework We have developed a testing scenario that involves multiple rounds of design activity for each subject, including ideation, paper-based and physical prototyping, testing, comparing, and Behavior engineering design activity • In situ, controlled single subject engineering design challenge • Video observation and recording Physiology – physiological data recorded during engineering design activity • EEG, ECG, Breathing wave amplitude, Heart Rate, Respiration Rate Psychology – cognitive preferences • KAI (Kirton Adaption-Innovation inventory) • Other psychometric instruments Engineering Design Cognitive Science