Experts vs. Novices: Differences in How Mental Representations are Used in Engineering Design (original) (raw)

2011, Journal of Technology Education

Mental representation is an important cognitive construct when solving engineering design problems. When students are given a design problem, they must decide what is known, the constraints they have to work with, and what is required by the customer. They then use mental representations, such as metaphors, analogies, and propositions, to make sense of the problem and develop a solution. Several studies have investigated the use of mental representations in problem solving. For example, Greca and Moreira (1997) investigated the use of mental models, propositions, and images by college students in solving physics problems involving electrical and magnetic fields. Their findings suggested that students work mostly with propositions unrelated to, or interpreted according to, mental models. Gick and Holyoak (1980) investigated the provision of source analogs prior to the tackling of a problem that is superficially different, but conceptually similar. Casakin and Goldschmidt (1999) examined the use of visual analogs by expert and novice designers in their work. The results of both studies indicated that people are good at utilizing prior problem and solution information when they are directed to do so, but then may not be efficient in detecting analogous information under unprompted conditions. Other studies (Holyoak & Koh, 1987; Keane, 1987) show that past analogies are more readily activated when there are surface similarities in the target problem and the analogy. Conceptual Framework Guiding the Study There are several types of mental representation, but for the purpose of this study propositions, metaphors, and analogies were investigated. A proposition refers to the smallest unit of knowledge that one can sensibly judge as true or false. According to Paivio (1990), propositions are the most versatile of representational concepts because they can be used to describe any type of information. They are strings of symbols that correspond to natural language. Unlike language, however, propositional representations are assumed to be "completely amodal, abstract, conceptual structures that represent information in the same way regardless of whether the information is experienced verbally, as a spoken or written sentence in whatever language, or nonverbally, as a perceptual scene" (Paivio, 1990, p. 31). The relevance of propositions for engineering