A novel systematic approach for analysing exploratory design ideation. (3rd March 2020)

• Record Type: Journal Article
• Authors: Hay, L.; Duffy, A. H. B.; Grealy, M.; Tahsiri, M.; McTeague, C.; Vuletic, T.
• Is Part Of: Journal of engineering design. Volume 31:Number 3(2020)
• Page Start: 127
• Page End: 149
• Publication Date: 2020-03-03
• Subjects: Creative design -- design novelty -- exploratory design -- novelty assessment -- novelty metrics; Engineering design -- Periodicals; Design, Industrial -- Periodicals; Industrial engineering -- Periodicals; 620.0042
• DOI: 10.1080/09544828.2019.1662381
• Languages: English
• ISSNs: 0954-4828

Abstract

ABSTRACT: Two kinds of design ideation process may be distinguished in terms of the problems addressed: (i) solution-focused, i.e. generating solutions to address a fixed problem specifying a desired output; and (ii) exploratory, i.e. considering different interpretations of an open-ended problem and generating associated solutions. Existing systematic analysis approaches focus on the former; the literature is lacking such an approach for the latter. In this paper, we provide a means to systematically analyse exploratory ideation for the first time through a new approach: Analysis of Exploratory Design Ideation (AEDI). AEDI involves: (1) open-ended ideation tasks; (2) coding of explored problems and solutions from sketches; and (3) evaluating ideation performance based on coding. We applied AEDI to 812 concept sketches from 19 open-ended tasks completed during a neuroimaging study of 30 professional product design engineers. Results demonstrate that the approach provides: (i) consistent tasks that stimulate problem exploration; (ii) a reliable means of coding explored problems and solutions; and (iii) an appropriate way to rank/compare designers' performance. AEDI enables the benefits of systematic analysis (e.g. greater comparability, replicability, and efficiency) to be realised in exploratory ideation research, and studies using open-ended problems more generally. Future improvements include increasing coding validity and reliability.