Decreasing the Effect of Verbal Noise in Analyzing Cognitive Activity of a Design Process

Abstract

In studying cognitive activity in design it is common practice to use designers' verbalizations during a design process to elicit the reasoning behind design actions. These verbalizations are segmented in order to enable a quantifiable analysis of the cognitive processes. Researchers have shown how Shannon's entropy can be applied to coded verbal data to provide a measure of creativity of those processes. We applied this method to a pilot study, investigating the effects of different design tools on creativity in the context of architectural design. Participants had to design three tasks of isomorphic nature, each with a different tool, in one design session. As shown a significant number of verbal comments were repetitions of already established ideas. Such comments brought nothing new to the sequence of activities but affected the value of information carried within that process which biased the measure of creativity. The paper regards these utterance as verbal noise. It proposes the use of corpus linguistic tools together with a coding scheme that can depict the hierarchical relationship of cognitive patterns used in the process to eliminate verbal noise from analysis. The method was applied to one participant's data, which shows a promising step in increasing the veracity of using verbal data in analyzing cognitive activity.