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A Systematic Brainstorming Ideation Method for Novice Designers based on SECI Theory

Part of: Design Creativity

Published online by Cambridge University Press:  26 July 2019

Taegyun Kim ,
Alison McKay  and
Briony Thomas

Abstract

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Design ideation is a critical early step in any design process and especially challenging for novice designers. This paper introduces the “Systematic Brainstorming Ideation (SBI)” method that, as part of a wider design ideation process, improves the range and number of design concepts generated by novice designers. In this paper we give a brief introduction to the design ideation method to set a context for SBI and then introduce SBI in more detail. Evaluation experiments with 101 novice designers, based in UK and South Korea, are reported. Results indicate a 30% improvement in the number of design concepts generated.

Keywords

Conceptual designDesign methodsEarly design phasesCase study

Information

Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 249 - 258
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Ball, L.J., Ormerod, T.C. and Morley, N.J. (2004), “Spontaneous analogising in engineering design: a comparative analysis of experts and novices”, Design Studies, Vol. 25 No. 5, pp. 495–508. https://doi.org/10.1016/j.destud.2004.05.004Google Scholar
Ball, L.J., St.B.T. Evans, J., Dennis, I. and Ormerod, T.C. (1997), “Problem-solving Strategies and Expertise in Engineering Design”, Thinking & Reasoning, Vol. 3 No. 4, pp. 247–270. https://doi.org/10.1080/135467897394284Google Scholar
Blessing, L.T.M. and Chakrabarti, A. (2009), DRM, a Design Research Methodology, Springer, Vol. 39, Springer London, London, available at: https://doi.org/10.1007/978-1-84882-587-1.Google Scholar
Borgianni, Y., Lenarduzzi, V., Rotini, F. and Taibi, D. (2018), “BRINGING STIMULATED IDEATION IN A WEB ENVIRONMENT: STUDENTS' EVALUATIONS OF A BASIC SOFTWARE RELEASE”, Bath, pp. 411–418.Google Scholar
Bork, D., Karagiannis, D. and Hawryszkiewycz, I. (2017), “Supporting Customized Design Thinking Using a Metamodel-based Approach Metamodel-based Approach for Customized Design Thinking Supporting Customized Design Thinking Using a Metamodel-based Approach”, 20th Australasian Conference on Information Systems (ACIS) 2017, pp. 1–11.Google Scholar
Cassotti, M., Agogué, M., Camarda, A., Houdé, O. and Borst, G. (2016), “Inhibitory Control as a Core Process of Creative Problem Solving and Idea Generation from Childhood to Adulthood”, New Directions for Child and Adolescent Development, Vol. 2016 No. 151, pp. 61–72. https://doi.org/10.1002/cad.20153Google Scholar
Chootongchai, S. and Songkram, N. (2018), “Design and Development of SECI and Moodle Online Learning Systems to Enhance Thinking and Innovation Skills for Higher Education Learners”, International Journal of Emerging Technologies in Learning (IJET), Vol. 13 No. 03, p. 154. https://doi.org/10.3991/ijet.v13i03.7991Google Scholar
Dinar, M., Shah, J.J., Cagan, J., Leifer, L., Linsey, J., Smith, S.M. and Hernandez, N.V. (2015a), “Empirical Studies of Designer Thinking: Past, Present, and Future”, Journal of Mechanical Design, Vol. 137 No. 2, p. 021101. https://doi.org/10.1115/1.4029025Google Scholar
Dinar, M., Shah, J.J., Park, Y. and Langley, P. (2015b), “PATTERNS OF CREATIVE DESIGN: PREDICTING IDEATION FROM PROBLEM FORMULATION”, pp. 1–10.Google Scholar
Dugosh, K.L., Paulus, P.B., Roland, E.J. and Yang, H.-C. (2000), “Cognitive stimulation in brainstorming”, Journal of Personality and Social Psychology, Vol. 79 No. 5, pp. 722–735. https://doi.org/10.1037/0022-3514.79.5.722Google Scholar
Farel, R. and Yannou, B. (2013), “Bio-Inspired Ideation: Lessons From Teaching Design To Engineering Students”, ICED13: 19th International Conference on Engineering Design, No. August, pp. 1–9.Google Scholar
Goldschmidt, G. and Smolkov, M. (2006), “Variances in the impact of visual stimuli on design problem solving performance”, Design Studies, Vol. 27 No. 5, pp. 549–569. https://doi.org/10.1016/j.destud.2006.01.002Google Scholar
Goucher-Lambert, K. and Cagan, J. (2017), “Using crowdsourcing to provide analogies for designer ideation in a cognitive study”, Proceedings of the International Conference on Engineering Design, ICED, Vol. 8 No. DS87-8, pp. 529–538.Google Scholar
Hatchuel, A., Le Masson, P., Reich, Y. and Subrahmanian, E. (2018), “Design theory: a foundation of a new paradigm for design science and engineering”, Research in Engineering Design, Springer London, Vol. 29 No. 1, pp. 5–21. https://doi.org/10.1007/s00163-017-0275-2Google Scholar
Hernandez, N.V., Shah, J.J. and Smith, S.M. (2010), “Understanding design ideation mechanisms through multilevel aligned empirical studies”, Design Studies, Vol. 31 No. 4, pp. 382–410. https://doi.org/10.1016/j.destud.2010.04.001Google Scholar
Hey, J., Linsey, J., Agogino, A.M. and Wood, K.L. (2008), “Analogies and Metaphors in Creative Design”, International Journal of Engineering Education, Vol. 24 No. 2, pp. 283–294.Google Scholar
Ho, C.-H. (2001), “Some phenomena of problem decomposition strategy for design thinking: differences between novices and experts”, Design Studies, Vol. 22 No. 1, pp. 27–45. https://doi.org/10.1016/S0142-694X(99)00030-7Google Scholar
Houdé, O. and Borst, G. (2014), “Measuring inhibitory control in children and adults: Brain imaging and mental chronometry”, Frontiers in Psychology, Vol. 5 No. JUN, pp. 1–7. https://doi.org/10.3389/fpsyg.2014.00616Google Scholar
Kavakli, M. and Gero, J.S. (2002), “The structure of concurrent cognitive actions: a case study on novice and expert designers”, Design Studies, Vol. 23 No. 1, pp. 25–40. https://doi.org/10.1016/S0142-694X(01)00021-7Google Scholar
Kohn, N.W. and Arditti, L.E. (2011), “Effects of Quantity and Quality Instructions on Brainstorming”, Vol. 45 No. 1, pp. 38–46. https://doi.org/10.1002/j.2162-6057.2011.tb01083.xGoogle Scholar
Koronis, G., Silva, A. and Kang, J. (2018), “Impact of Design Briefs on Creativity : a Study on Measuring Student Designers Outcomes”, pp. 2461–2472.Google Scholar
Mohamad, N.A., Anwar, K., Khaidzir, M. and Ibrahim, R. (2016), “A Study on Transforming the Knowledge in Design Learning Environment”, No. August, pp. 29–30.Google Scholar
Moreno, D., Blessing, L., Wood, K., Vögele, C. and Hernández, A. (2015a), “Creativity Predictors: Findings From Design-by-Analogy Ideation Methods’ Learning and Performance”, 27th International Conference on Design Theory and Methodology, ASME, Boston, USA. https://doi.org/10.1115/DETC2015-47929Google Scholar
Moreno, D.P., Yang, M.C., Hernández, A.A., Linsey, J.S. and Wood, K.L. (2015b), “A Step Beyond to Overcome Design Fixation: A Design-by-Analogy Approach”, Design Computing and Cognition ‘14, Springer International Publishing, Cham, pp. 607–624. https://doi.org/10.1007/978-3-319-14956-1_34Google Scholar
Nonaka, I., Toyama, R. and Konno, N. (2000), “SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation”, Long Range Planning, Vol. 33 No. 1, pp. 5–34. https://doi.org/10.1016/S0024-6301(99)00115-6Google Scholar
Orthel, B.D. and Day, J.K. (2016), “Processing Beyond Drawing : A Case Study Exploring Ideation for Teaching Design”, SAGE Open, Vol. 6 No. 3, pp. 1–16. https://doi.org/10.1177/2158244016663285Google Scholar
Sakellariou, E., Karantinou, K. and Goffin, K. (2017), “‘Telling tales’: Stories, metaphors and tacit knowledge at the fuzzy front-end of NPD”, Creativity and Innovation Management, Vol. 26 No. 4, pp. 353–369. https://doi.org/10.1111/caim.12237Google Scholar
Self, J., Evans, M. and Kim, E.J. (2016), “A comparison of digital and conventional sketching: Implications for conceptual design ideation”, Journal of Design Research, Vol. 14 No. 2, pp. 171–202. http://doi.org/10.1504/JDR.2016.077028Google Scholar
Shah, J. (2003), “Metrics for measuring ideation effectiveness”, Design Studies, Vol. 24 No. 2, pp. 111–134. https://doi.org/10.1016/S0142-694X(02)00034-0Google Scholar
Valkenburg, R. and Dorst, K. (1998), “The reflective practice of design teams”, Design Studies, Vol. 19 No. 3, pp. 249–271. https://doi.org/10.1016/S0142-694X(98)00011-8Google Scholar
Venkataraman, S., Binyang, S., Jianxi, L., Karupppasamy, S., Elara, M.R., Blessing, L. and Wood, K. (2017), “Investigating Effects of Stimuli on Ideation Outcomes”, International Conference on Engineering Design.Google Scholar
Whelan, L., Maher, C. and Deevy, C. (2017), “Towards a University Design School. Restoring the value of tacit knowledge through assessment”, The Design Journal, Routledge, Vol. 20 No. sup1, pp. S1459–S1470.Google Scholar
Wilson, J.O., Rosen, D., Nelson, B.A. and Yen, J. (2010), “The effects of biological examples in idea generation”, Design Studies, Elsevier Ltd, Vol. 31 No. 2, pp. 169–186. https://doi.org/10.1080/14606925.2017.1352670Google Scholar