A novel systematic approach for analysing exploratory design ideation

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 openended 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.

The neural correlates of ideation in product design engineering practitioners

“…In turn, it is not clear to what degree the novelty scores calculated based on the coding reflect the participants’ ideation processes versus the coders’ interpretations (Hay et al. 2019 b ). As noted in Section 3.2, we did not observe a relationship between concept novelty and brain activation during ideation, which seems counterintuitive given that a key goal of ideation is to generate new ideas (Benedek et al.…”

“…On average, the tasks were rated as moderately difficult, with a mean rating of 3.76 (SD = 1.08) for professionals and 3.80 (SD = 0.74) for students (Hay et al. 2019 b ).…”

“…Sketches were interpreted to determine whether they conveyed solutions to the open-ended and constrained problems presented during the study through a qualitative coding process described in detail in Hay et al. (2019 b ). Coding was completed using the NVivo software package (QSR International 2018).…”

“…Finally, to ensure that the ideation tasks were matched in difficulty, we asked designers to rate the perceived difficulty of each one on a scale from 1 (very easy) to 7 (very difficult). On average, the tasks were rated as moderately difficult, with a mean rating of 3.76 (SD = 1.08) for professionals and 3.80 (SD = 0.74) for students (Hay et al 2019b).…”

“…Whilst there are questions regarding how reflective these sketches are of the ideas actually generated during the tasks (discussed in Section 4), they at least provide an indication in a context where it is difficult to gather more conventional evidence. Sketches were interpreted to determine whether they conveyed solutions to the open-ended and constrained problems presented during the study through a qualitative coding process described in detail in Hay et al (2019b). Coding was completed using the NVivo software package (QSR International 2018).…”