Chun-Juei Chou
Department of Industrial Design, National Cheng Kung University, Taiwan
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Ingår i: KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13
Linköping Electronic Conference Proceedings 100:40, s. 495-502
Publicerad: 2014-06-11
ISBN: 978-91-7519-276-5
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
For innovation; sometimes it is necessary to imagine future lifestyles in order to design corresponding products; services; or systems. However; it is very difficult for design students to characterize the future and there is no such simple method to help them to do so reasonably. This paper hypothesizes that future is predictable based on historical contexts and any future lifestyle is the extension or the contrary of the current one. For easily predicting future lifestyles; this paper proposes three heuristic ways. They are Analogical Reasoning (AR); Timeframe Reasoning (TR); and Causal Relationship Reasoning (CRR). Each of the reasoning approaches provides a simple way of imagining a specific future lifestyle. The formula of AR is “A1 : B1 :: A2 : B2”. The formula of TR is “Now > Next > Future > Ideal”. In addition; the formula of CRR is “Cause 1 > Effect 1 = Cause 2 > Effect 2”. Obviously; they help to infer future lifestyles in different ways of thinking. There are four items in each of the three approaches. The designer who applies any of the three approaches must define the first three items and then infer the last one as a particular future lifestyle. These three heuristic approaches are taught in several courses including Sensational Product Engineering; Form Design; and Color Design. This research finds that both graduate and undergraduate students in Industrial Design can apply AR; TR and CRR to efficiently generate uncommon but reasonable ideas of vivid future lifestyles.
Altshuller; G. S. (1984). Creativity as an Exact Science. Gorden and Breach; Luxembourg; 272.
Ball; L.J.; Ormerod; T.C.; & Morley; N.J. (2004). Spontaneous analogising in engineering design: A comparative analysis of experts and novices. Design Studies; 25; 495-508.
Casakin; H.; & Goldschmidt; G. (1999) Expertise and the use of visual analogy: implications for design education. Design Studies; 20; 153-175.
Chi; M. T. H.; Feltovich; P. J.; & Glaser; R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science; 5; 121-152.
FutureTimeline.net (n.d.). Historical Timeline. Retrieved Jan 28; 2014; from FutureTimeline.net Website: http://www.futuretimeline.net/index.htm
Gentner; D.; & Markman A. B. (1997). Structure Mapping in Analogy and Similarity. American Psychologist; 52; 45-56.
Hey; J.; Linsey; J.; Agogino; A. M.; & Wood; K. L. (2008). Analogies and Metaphors in Creative Design. International Journal of Engineering Education; 24(2); 283-294.
McAdams; D. A.; Wood K. L. (2002). A Quantitative Similarity Metric for Design-by-Analogy. Journal of Mechanical Design; 124; 173-182; DOI: 10.1115/1.1475317.
Pierce; K. A.; & Gholson; B. (1994). Surface similarity and relational similarity in the development of analogical problem-solving: isomorphic and nonisomorphic transfer. Developmental Psychology; 14(3); 724-737.
SAP (2013). 15 Trends That Are Shaping The Future. Retrieved Jan 29; 2014; from Business Insider Website: http://www.businessinsider.com/sc/15-trends-that-are-shaping-the-future-2013-11?op=1
Shuttleworth; M. (2009). Prediction in Research. Retrieved Jan 29; 2014; from Explorable.com Website: http://explorable.com/prediction-in-research
Vosniadou; S. & Ortony; A. (1989). Similarity and analogical reasoning: a synthesis. Similarity and analogical reasoning. Cambridge University Press; Cambridge; 1-17.
Wikipedia (2014a). Transporter (Star Trek). Retrieved Jan 30; 2014; from Wikipedia; the free encyclopedia Website: http://en.wikipedia.org/wiki/Transporter_(Star_Trek)
Wikipedia (2014b). Prediction. Retrieved Jan 28; 2014; from Wikipedia; the free encyclopedia Website: http://en.wikipedia.org/wiki/Prediction
