Hostname: page-component-77f85d65b8-g4pgd Total loading time: 0 Render date: 2026-03-29T17:00:37.616Z Has data issue: false hasContentIssue false
  • English
  • Français

Semantic Analysis Approach to Studying Design Problem Solving

Part of: Human Behaviour in Design and Design Cognition

Published online by Cambridge University Press:  26 July 2019

Georgi V. Georgiev  and
Danko D. Georgiev
Georgi V. Georgiev*
Affiliation:
Center for Ubiquitous Computing, University of Oulu, Finland;
Danko D. Georgiev
Affiliation:
Institute for Advanced Study, Varna, Bulgaria
*
Contact: Georgiev, Georgi V., University of Oulu, Center for Ubiquitous Computing, Finland, georgi.georgiev@oulu.fi

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

To objectively and quantitatively study transcribed protocols of design problem solving conversations, we propose a semantic analysis approach based on dynamic semantic networks of nouns constructed with WordNet 3.1 lexical database. We examined the applicability of the semantic approach focused on a dynamic evaluation of the design problem solving process in educational settings. Using a case of real- world design problem-solving conversations, we show that the approach is able to determine the time dynamics of semantic factors such as level of abstraction, polysemy or information content, and quantify convergence/divergence of semantic similarity in design conversations between students, instructors and real clients. The approach can also be used to evaluate the aforementioned semantic factors for successful and unsuccessful ideas generated in the process of design problem solving, or to assess the effect of external feedback on the developed design solution. The proposed semantic analysis approach allows fast computation of the semantic factors in real time thereby demavonstrating a potential for both monitoring and support of the design problem solving process.

Keywords

Design cognitionDesign processHuman behaviour in designSemantic analysisDesign conversations

Information

Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 1823 - 1832
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

Acar, S. and Runco, M.A. (2014), “Assessing associative distance among ideas elicited by tests of divergent thinking”, Creativity Research Journal, Vol. 26 No. 2, pp. 229–238. http://doi.org/10.1080/10400419.2014.901095Google Scholar
Adams, R.S. (2015). “Design review conversations: The dataset” in Adams, R. S. and Siddiqui, J. A., eds., Analyzing Design Review Conversations, Indiana: Purdue University Press, West Lafayette.Google Scholar
Adams, R.S. and Siddiqui, J.A. (2013), Purdue DTRS – Design Review Conversations Database, XRoads Technical Report, TR-01-13, Indiana: Purdue University, West Lafayette.Google Scholar
Badke-Schaub, P. (2004), “Strategies of experts in engineering design: between innovation and routine behaviour”, Journal of Design Research, Vol. 4 No. 2, pp. 125–143. http://doi.org/10.1504/jdr.2004.009837Google Scholar
Beketayev, K. and Runco, M.A. (2016), “Scoring divergent thinking tests by computer with a semantics-based algorithm”, Europe's Journal of Psychology, Vol. 12 No. 2, pp. 210–220. http://doi.org/10.5964/ejop.v12i2.1127Google Scholar
Bird, S., Klein, E. and Loper, E. (2009), Natural Language Processing with Python, Sebastopol, O'Reilly Media, California.Google Scholar
Blanchard, E., Harzallah, M. and Kuntz, P. (2008), “A generic framework for comparing semantic similarities on a subsumption hierarchy” in Ghallab, M., Spyropoulos, C. D., Fakotakis, N. and Avouris, N., eds., ECAI 2008: 18th European Conference on Artificial Intelligence including Prestigious Applications of Intelligent Systems (PAIS 2008), Greece: IOS Press, Patras, pp. 20–24.Google Scholar
Boden, M.A. (2004), “The Creative Mind: Myths and Mechanisms”, 2nd ed., Routledge, London.10.4324/9780203508527Google Scholar
Casakin, H. and Goldschmidt, G. (1999), “Expertise and the use of visual analogy: implications for design education”, Design Studies, Vol. 20 No. 2, pp. 153–175. http://doi.org/10.1016/S0142-694X(98)00032-5Google Scholar
Cash, P., Stanković, T. and Štorga, M. (2014), “Using visual information analysis to explore complex patterns in the activity of designers”, Design Studies, Vol. 35 No. 1, pp. 1–28. http://doi.org/10.1016/j.destud.2013.06.001Google Scholar
Dong, A. (2005), “The latent semantic approach to studying design team communication”, Design Studies, Vol. 26 No. 5, pp. 445–461. http://doi.org/10.1016/j.destud.2004.10.003Google Scholar
Dong, A. (2007), “The enactment of design through language”, Design Studies, Vol. 28 No. 1, pp. 5–21. http://doi.org/10.1016/j.destud.2006.07.001Google Scholar
Dong, A. (2009), The Language of Design: Theory and Computation, Springer, London.Google Scholar
Fellbaum, C. (1998), WordNet: An Electronic Lexical Database, The MIT Press, Cambridge, Massachusetts.Google Scholar
Georgiev, G.V. and Georgiev, D.D. (2018), “Enhancing user creativity: semantic measures for idea generation”, Knowledge-Based Systems, Vol. 151, pp. 1–15. http://doi.org/10.1016/j.knosys.2018.03.016Google Scholar
Georgiev, G.V., Nagai, Y. and Taura, T. (2008), “Method of design evaluation focused on relations of meanings for a successful design”, in Marjanovic, D., Storga, M., Pavkovic, N. and Bojcetic, N., eds., 10th International Design Conference, DESIGN 2008, Dubrovnik, Croatia, May 19-22, 2008, The Design Society, pp. 1149–1158.Google Scholar
Georgiev, G.V., Nagai, Y. and Taura, T. (2010), “A method for the evaluation of meaning structures and its application in conceptual design”, Journal of Design Research, Vol. 8 No. 3, pp. 214–234. http://doi.org/10.1504/jdr.2010.032607Google Scholar
Georgiev, G.V. and Taura, T. (2014), “Polysemy in design review conversations” in 10th Design Thinking Research Symposium, Purdue University, West Lafayette, Indiana: Purdue University.Google Scholar
Goldschmidt, G. (2014), Linkography: Unfolding the Design Process, MIT Press, Cambridge, Massachusetts.Google Scholar
Goldschmidt, G. (2016), “Linkographic evidence for concurrent divergent and convergent thinking in creative design”, Creativity Research Journal, Vol. 28 No. 2, pp. 115–122. http://doi.org/10.1080/10400419.2016.1162497Google Scholar
Goldschmidt, G., Casakin, H., Avidan, Y. and Ronen, O. (2014), “Three studio critiquing cultures: Fun follows function or function follows fun?” in 10th Design Thinking Research Symposium, Purdue University, Indiana: Purdue University, West Lafayette.Google Scholar
Hatcher, G., Ion, W., Maclachlan, R., Marlow, M., Simpson, B., Wilson, N. and Wodehouse, A. (2018), “Using linkography to compare creative methods for group ideation”, Design Studies, Vol. 58, pp. 127–152. http://doi.org/10.1016/j.destud.2018.05.002Google Scholar
Kan, J.W.T. and Gero, J.S. (2017), Quantitative Methods for Studying Design Protocols, Springer, Dordrecht.10.1007/978-94-024-0984-0Google Scholar
Loria, S. (2016), TextBlob: Simplified Text Processing, Center for Open Science, Charlottesville, Virginia.Google Scholar
Mabogunje, A. and Leifer, L.J. (1997), “Noun phrases as surrogates for measuring early phases of the mechanical design process”, in 1997 ASME Design Engineering Technical Conferences: DETC ’97, Sacramento, California, September 14–17, 1997, American Society of Mechanical Engineers.Google Scholar
Nagai, Y., Taura, T. and Mukai, F. (2009), “Concept blending and dissimilarity: factors for creative concept generation process”, Design Studies, Vol. 30 No. 6, pp. 648–675. http://doi.org/10.1016/j.destud.2009.05.004Google Scholar
Nickerson, J.V., Corter, J.E., Tversky, B., Rho, Y.-J., Zahner, D. and Yu, L. (2013), “Cognitive tools shape thought: diagrams in design”, Cognitive Processing, Vol. 14 No. 3, pp. 255–272. http://doi.org/10.1007/s10339-013-0547-3Google Scholar
Olteţeanu, A.-M. and Falomir, Z. (2015), “comRAT-C: A computational compound Remote Associates Test solver based on language data and its comparison to human performance”, Pattern Recognition Letters, Vol. 67 No. 1, pp. 81–90. http://doi.org/10.1016/j.patrec.2015.05.015Google Scholar
Resnik, P. (1999), “Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language”, Journal of Artificial Intelligence Research, Vol. 11, pp. 95–130.10.1613/jair.514Google Scholar
Segers, N.M., de Vries, B. and Achten, H.H. (2005), “Do word graphs stimulate design?”, Design Studies, Vol. 26 No. 6, pp. 625–647. http://doi.org/10.1016/j.destud.2005.05.002Google Scholar
Taura, T. and Nagai, Y. (2013), Concept Generation for Design Creativity: A Systematized Theory and Methodology, Springer, London.Google Scholar
Taura, T., Yamamoto, E., Fasiha, M.Y.N., Goka, M., Mukai, F., Nagai, Y. and Nakashima, H. (2012), “Constructive simulation of creative concept generation process in design: a research method for difficult-to-observe design-thinking processes”, Journal of Engineering Design, Vol. 23 No. 4, pp. 297–321. http://doi.org/10.1080/09544828.2011.637191Google Scholar
Wilkenfeld, M.J. and Ward, T.B. (2001), “Similarity and emergence in conceptual combination”, Journal of Memory and Language, Vol. 45 No. 1, pp. 21–38. http://doi.org/10.1006/jmla.2000.2772Google Scholar
Yamamoto, E., Goka, M., Yusof, N.F.M., Taura, T. and Nagai, Y. (2009), “Virtual modeling of concept generation process for understanding and enhancing the nature of design creativity”, in Norell Bergendahl, M., Grimheden, M., Leifer, L., Skogstad, P. and Lindemann, U., eds., 17th International Conference on Engineering Design, Vol. 2, Design Theory and Research Methodology, Palo Alto, CA, August 24-27, 2009, The Design Society, pp. 101–112.Google Scholar