Domain knowledge and problem framing in engineering design: sequential decision making

Abstract
The importance of domain knowledge and problem framing in design cognition is well established; the relationship between these factors, constraint-boundary understanding, model-derived information-acquisition behavior, and design performance in the context of the SIADM framework has not been examined extensively across different types of participants. In particular, there is insufficient empirical evidence on the role of these factors in a sequential information-acquisition decision-making task. This paper aims to address this by (1) adopting an existing SIADM model to make decisions when provided with information through a bounded-rational, myopic expected improvement decision rule, and (2) empirically assessing this model through a controlled experiment. The experiment measures an individual's domain knowledge using a Concept Inventory test, and the treatment variable is controlled by problem framing. Participants are given a design optimization challenge in two distinct approaches to address the research question: a Track Design Problem (TDP), presented as a domain-specific task, and a function-optimization problem (FOP). The result is interpreted in the context of the adopted SIADM framework and shows that the association between domain knowledge and domain-specific framing is associated with improved design outcomes, while the expected-improvement-rule is considered a descriptive approximation rather than a model of human decision-making.