Creativity and Design: Creativity's New Definition and its Relationship to Design (original) (raw)

Nascent directions for design creativity research

International Journal of Design Creativity and Innovation

Design is recognized as one of the creative professions but that does not mean that design equals creativity. Much of design is not creative, rather it is routine in the sense that the designs produced are those that are similar to existing designs and are only unique in terms of the situation they are in. However, there is value in producing designs that are considered creative in that they add significant value and change people's perceptions and, in doing so, have the potential to change society by changing its value system. A search for the terms 'design' and 'creativity' in books over the last 200 years (using Google's Ngram) shows that the term "design' was well established by 1800 and its use dropped between 1800 and 1900, after which its use increased to 2000. The term 'creativity' only came into noticeable use from 1940 on (Figure 1). It is, therefore, not surprising that creativity research is a young field. Much of early design creativity research has focused on distinguishing design creativity from designing; typically, by attempting to determine when and how a designer was being creative while they were designing. This still remains an important area of design creativity research that deserves considerable attention. Much of the design creativity research over the last 30-40 years has focused on either cognitive studies of designers or on building computational models of creative processes, generally using artificial intelligence or cognitive models. As in other areas of design research, there has been interest in developing cognitive creativity support tools. These two paradigmatic approaches have yielded interesting and important results. Tools can be categorized along a spectrum from passive through responsive to active. Passive tools need to be directly invoked by the designer and remain unchanged by their use. A spreadsheet is an exemplary example of a general passive tool. Passive tools that support design creativity include, for example, morphological analysis and TRIZ. Responsive tools need to be directly invoked by the designer but are changed by their use and do so by learning (Gero, 1996). They aim to tailor their response to the user over time. They tend to be developed for a specific purpose and are often proprietary. Active tools interact with the designer, i.e., they respond to what the designer is doing and make proposals. More recently, there has been interest in studying creativity when the designer is using responsive and active creativity aids. These aids cover a wide spectrum. Here two new categories will be considered: artificial intelligence that supports co-creation and neuro-based creativity enhancement. These two approaches form the basis of two nascent directions that are fundamentally different to the current directions of cognitive studies and passive cognitive support tools. In addition, there have been studies with drugs that affect the brain and that anecdotally enhance creativity. Alcohol has been shown to have a mild positive effect on the remote association creativity test but impairs divergent thinking, which is involved in design creativity (Norlander, 1999). However, controlled studies with Ritalin (methylphenidate) (Baas et al., 2020), cannabis (tetrahydrocannabinol) (Kowal et al., 2015) and LSD (lysergic acid diethylamide) Figure 1. Google's Ngram on the appearance of the terms "design" (blue line) and "creativity" (red line) in books since 1800.

Future Directions for Design Creativity Research

Design Creativity 2010, 2011

This paper commences with a brief overview of where the creativity may lie in the enterprise of designing artifacts. It puts forward the concept that design creativity is not a unitary concept and needs to be treated multi-dimensionally by stating that design creativity may be in multiple locations. The paper then proceeds to present a brief overview of what has been researched and how it is has been researched. It classifies what has been researched under: design processes, cognitive behavior and interactions. This is followed by the articulation of future directions for design creativity research in the areas of: design processes; cognitive behavior, social interaction; cognitive neuroscience; measuring design creativity and test suites of design tasks.

By measure: creativity in design

Industry and Higher Education, 2007

Specific training may be required to develop creativity in design students. At the very least, training is valuable in developing creativity in first-year students. Creativity is a skill that can be examined, used and taught -and it is one that is central to designing. This paper presents the results of empirical research from a class in creative problem solving for design students. The nature of creativity and the structure of the class are described, and this is followed by an outline of the research methodology and the use of the verbal Torrance Test of Creative Thinking. Creativity, as measured through the test, significantly increased.

Creativity in the Design Process

Springer Series in Design and Innovation, 2022

Springer Series in Design and Innovation (SSDI) publishes books on innovation and the latest developments in the fields of Product Design, Interior Design and Communication Design, with particular emphasis on technological and formal innovation, and on the application of digital technologies and new materials. The series explores all aspects of design, e.g. Human-Centered Design/User Experience, Service Design, and Design Thinking, which provide transversal and innovative approaches oriented on the involvement of people throughout the design development process. In addition, it covers emerging areas of research that may represent essential opportunities for economic and social development. In fields ranging from the humanities to engineering and architecture, design is increasingly being recognized as a key means of bringing ideas to the market by transforming them into user-friendly and appealing products or services. Moreover, it provides a variety of methodologies, tools and techniques that can be used at different stages of the innovation process to enhance the value of new products and services. The series' scope includes monographs, professional books, advanced textbooks, selected contributions from specialized conferences and workshops, and outstanding Ph.D. theses.

Creativity in the engineering design process

2007

It is accepted that innovation is key to any company's long term success. Despite this there are few published engineering design processes with the inclusion, mention or consideration of the creative process. With a strong body of research from the social sciences based upon the different creative processes, it is argued that engineering design research should embrace these processes in order to effectively adopt the tools, methods and techniques that have been developed around them. In this paper it is argued that the design process and the creative process are not synonymous, but it instead will consider creativity as an essential element in designing [1]. Over 100 different design and creative processes have been analysed and considered in total, 42 of which have been tabulated for comparative purposes within this paper. The linear style in which the majority of the process models are presented enabled easy comparison of the terminology. By extracting the key phases from both types of process, a descriptive process model is proposed describing creative process as a cyclical subset of the engineering design process. The overall purpose of this paper is to identify where and when in the process of design does creativity occur.

DESIGN CREATIVITY: REFINING THE MODEL

2009

The work of Margaret Boden (1990; 1994) is familiar to everyone involved in the field of Computational Creativity. Her work, although at times philosophical, opened up new areas of research about creativity. However, some (Haase, 1995; Ram et al., 1995) have criticized the lack of detail in her models of creativity. Making a general model more detailed can remove some of the subjectivity; allow more options for a model to be tested; and, of interest to this workshop, move closer to models that concern designing.

A generic model for creativity and innovation: overview for early phases of engineering design

This paper explores how 'creativity' and 'innovation' are most usefully modelled for the modern design context invariably consisting of conflicting technical, economical, organisational and social demands. Section 2 summarises the experiences and observations of engineers and the most comprehensive theories of creativity and innovation proposed by psychologists and educators, which set the stage for a generic model. Section 3 evaluates and synthesises the scope and use of over 100 commercially available tools to enhance creativity and innovation. We place this in the context of the 'processes of creating' outlined in the psychological literature as well as those generally accepted to lead to internationally competitive outcomes in engineering, business, sociology and literature, among others. The series of tables defines a preliminary Taxonomy of Tools to enable potential users to clarify how and where additional information or help should be solicited, to streamline any stage of engineering design. Section 4 elucidates a 'process of creating' as a generic model, which illustrates how contradictory input data become novel outcomes in processes that co-evolve the bodies of knowledge on both sides of a problem-solution equation. The model, in contrast to previous theories, is not vague -apparent contradictions between design demands can be resolved in precise steps, as long as the starting point of all actors/stakeholders is made coincident.

A quantitative approach for assessment of creativity in product design

Advanced Engineering Informatics, 2014

Most of the assessment of creativity in product design is based on the outcome, not the design process from which the creative ideas are derived. In this paper, we revealed the correlation coefficient of 20 factors critical in the product design process and the quality of design creativity via investigation of the design processes and outcomes of 30 senior student designers. Six closely related factors were identified as variables to calculate the design creativity. An assessment formula was proposed: the corresponding correlation coefficient is the weight factor of each variable, and the sum represents the design creativity degree. Our quantitative approach can improve the validity and reliability of assessment of creativity in product design.

Creativity in Design Engineers: Attitudes, Opinions and Potentially Influential Factors – Part II

Proceedings of the Canadian Engineering Education Association (CEEA), 2018

In the latter half of 2015, a survey looking at attitudes and beliefs about creativity was distributed on the campus of the University of Saskatchewan. Over 2000 responses were gathered, including more than 200 in the College of Engineering. Initial quantitative results from this study were reported in 2016 in Neufeld et al [2]. In terms of the methods used in the study, as discussed in Neufeld et al [2], an online pilot survey was distributed to students and faculty from a variety of the Colleges at the University. Survey questions probed respondents' affinity for creativity, their personality characteristics, their opinions on state, trait and skill-based viewpoints on creativity, and demographic details. The first part of the survey was a validated Creative Attitudes and Values measurement tool (part of the Runco Creativity Assessment Battery (rCAB) © 2012), as discussed in Acar and Runco [1]. This tool consists of 25, 5-point Likert scale items. Of these 25 items, 15 and 10 were indicative and contraindicative items, respectively. Contraindicative items were reverse coded so that they could be used along with the indicative ones. Both past research and our results showed good inter-item reliability scores for this measurement tool. In Neufeld et al [2] we presented results covering all of the closed-form, quantitative questions along with some correlational calculations with the rCAB scores. The focus of the current paper is on the qualitative results, as well as on a factor analysis of the rCAB questions. The factor analysis was quite successful. We used SPSS and forced a correlation of items, reducing to three factors. We have just over 29% of variance accounted for, with 10% non-redundant residuals. We have strong anticorrelation between one factor and the other two, and no correlation between the other two. These results will be compared to those of the rCAB authors [3]. As for the qualitative data, we asked several openended questions to probe how respondents defined creativity, whether they regarded it as a positive behavior, as well as how they felt about creativity in terms of it being a skill, trait and/or state. For example, pairs of questions asked when creativity is difficult and easy, when it should and should not be used, and when it grows and diminishes. For each of the 9 questions that had open-ended answers, concepts were extracted from individual responses. Concepts were then grouped into themes. Themes and concepts were compared across questions and were aligned. Responses were then coded for concepts and themes. At this point, the text data could be quantitatively examined. This paper presents those results, and discusses the implications of the concepts, themes, and their statistics for how we talk about creativity, and how we can teach it. Comparisons will be made between the results from engineering students and staff versus non-engineers. This paper completes the first level of evaluation of the results of this initial survey focused on attitudes and beliefs about creativity. Future work will focus on examining correlations between the results of different questions, including the rCAB scores.