Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-27T05:44:14.903Z Has data issue: false hasContentIssue false
  • English
  • Français

Investigation on the Aha-Experience as an Indicator of Correct Solutions in Functional Analysis in Engineering Design

Published online by Cambridge University Press:  27 July 2021

Christoph Zimmerer ,
Thomas Nelius  and
Sven Matthiesen
Christoph Zimmerer*
Affiliation:
Karlsruhe Institute of Technology
Thomas Nelius
Affiliation:
Karlsruhe Institute of Technology
Sven Matthiesen
Affiliation:
Karlsruhe Institute of Technology
*
Zimmerer, Christoph, Karlsruhe Institute of Technology (KIT), IPEK Institute of Product Engineering, Germany, christoph.zimmerer@kit.edu

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.

The functional analysis of technical systems is an important part of the design process. To further improve the design process, especially the functional analysis, it must not be viewed as a monodisciplinary process. To this end, cognitive factors such as the aha-experience must also be included in studies of analysis processes to a greater extent. This paper investigates the relationship between the occurrence of aha-experiences and the correctness of solutions in the analysis of a technical system. An aha-experience is a strong feeling of subjective certainty that accompanies the cognitive process of suddenly finding a previously unknown solution. For this purpose, a study on the functional analysis was evaluated. The results show that many identified subfunctions of the system under investigation were identified with an aha-experience and that these subfunctions are more often correct. The results also suggest that aha-experiences occur more often among students than among experienced design engineers. Especially among students, a positive relation of aha-experiences on the correctness of the identified subfunction can be seen. This offers potential for further investigations to make aha-experiences useful in design methods.

Keywords

Design cognitionHuman behaviour in designDesign engineeringfunctional analysisaha-experience
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 1947 - 1956
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), 2021. Published by Cambridge University Press

References

Akin, O. and Akin, C. (1996), “Frames of reference in architectural design: analysing the hyperacclamation (Aha-!)”, Design Studies, Vol. 17 No. 4, pp. 341–361.10.1016/S0142-694X(96)00024-5CrossRefGoogle Scholar
Ash, I.K., Jee, B.D. and Wiley, J. (2012), “Investigating Insight as Sudden Learning”, The Journal of Problem Solving, Vol. 4 No. 2. 10.7771/1932-6246.1123.10.7771/1932-6246.1123CrossRefGoogle Scholar
Badke-Schaub, P. and Frankenberger, E. (1999), “Analysis of design projects”, Design Studies, Vol. 20 No. 5, pp. 465–480. 10.1016/S0142-694X(99)00017-4.10.1016/S0142-694X(99)00017-4CrossRefGoogle Scholar
Bilalić, M., Graf, M., Vaci, N. and Danek, A.H. (2019), “The temporal dynamics of insight problem solving – restructuring might not always be sudden”, Thinking & Reasoning, Vol. 11 No. 3, pp. 1–37. 10.1080/13546783.2019.1705912.Google Scholar
Bock, A. (1955), “Die Begriffe “Konstruieren, Entwerfen und Gestalten””, Die Technik: technischwissenschaftliche Zeitschrift für Grundsatz- und Querschnittsfragen, Vol. 10 No. 8, pp. 504–505.Google Scholar
Booth, J.W., Reid, T.N., Eckert, C. and Ramani, K. (2015), “Comparing Functional Analysis Methods for Product Dissection Tasks”, Journal of Mechanical Design, Vol. 137 No. 8, p. 27. 10.1115/1.4030232.10.1115/1.4030232CrossRefGoogle Scholar
Bühler, K. (1907), “Tatsachen zu einer Psychologie der Denkvorgänge. I Über Gedanken”, Archiv für die gesamte Psychologie, Vol. 9, pp. 297–365.Google Scholar
Chrysikou, E.G. and Gero, J.S. (2020), “Using neuroscience techniques to understand and improve design cognition”, AIMS Neuroscience, Vol. 7 No. 3, pp. 319–326. 10.3934/Neuroscience.2020018.10.3934/Neuroscience.2020018CrossRefGoogle ScholarPubMed
Cohen, J. (1960), “A Coefficient of Agreement for Nominal Scales”, Educational and sychological measurement, Vol. 20 No. 1, pp. 37–46.10.1177/001316446002000104CrossRefGoogle Scholar
Cranford, E.A. and Moss, J. (2012), “Is Insight Always the Same? A Protocol Analysis of Insight in Compound Remote Associate Problems”, The Journal of Problem Solving, Vol. 4 No. 2. 10.7771/1932-6246.1129.10.7771/1932-6246.1129CrossRefGoogle Scholar
Cross, N., “Design cognition: Results from protocol and other empirical studies of design activity”, Design knowing and learning: Cognition in design education, pp. 79–103.10.1016/B978-008043868-9/50005-XCrossRefGoogle Scholar
Danek, A.H., Fraps, T., Müller, A. von, Grothe, B. and Ollinger, M. (2013), “Aha! experiences leave a mark: facilitated recall of insight solutions”, Psychological Research, Vol. 77 No. 5, pp. 659–669. 10.1007/s00426-012-0454-8.10.1007/s00426-012-0454-8CrossRefGoogle Scholar
Danek, A.H., Fraps, T., Müller, A. von, Grothe, B. and Ollinger, M. (2014), “Working wonders? investigating insight with magic tricks”, Cognition, Vol. 130 No. 2, pp. 174–185. 10.1016/j.cognition.2013.11.003.10.1016/j.cognition.2013.11.003CrossRefGoogle ScholarPubMed
Danek, A.H. and Salvi, C. (2018), “Moment of Truth: Why Aha! Experiences are Correct”, The Journal of Creative Behavior, Vol. 9, pp. 322–324. 10.1002/jocb.380.Google Scholar
Danek, A.H. and Wiley, J. (2016), “What about False Insights? Deconstructing the Aha! Experience along Its Multiple Dimensions for Correct and Incorrect Solutions Separately”, Frontiers in Psychology, Vol. 7, p. 2077. 10.3389/fpsyg.2016.02077.Google ScholarPubMed
Eckert, C., Ruckpaul, A., Alink, T. and Albers, A. (2012), “Variations in functional decomposition for an existing product: Experimental results”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 26 No. 2, pp. 107–128. 10.1017/S0890060412000029.10.1017/S0890060412000029CrossRefGoogle Scholar
Ericsson, K.A. and Simon, H.A. (1993), Protocol analysis – Verbal reports as data, MIT Press, Cambridge, Massachusetts.10.7551/mitpress/5657.001.0001CrossRefGoogle Scholar
Fleck, J.I. and Weisberg, R.W. (2004), “The use of verbal protocols as data: An analysis of insight in the candle problem”, Memory & Cognition, Vol. 32 No. 6, pp. 990–1006.10.3758/BF03196876CrossRefGoogle ScholarPubMed
Gericke, K. and Blessing, L. (2012), “An analysis of design process models across disciplines”, DS 70: Proceedings of DESIGN 2012, the 12th International Design Conference, Dubrovnik, Croatia.Google Scholar
Hacker, W. (2002), “Konstruktives Entwickeln: Psychologische Grundlagen”, in Hacker, W. (Ed.), Denken in der Produktentwicklung: psychologische Unterstützung der frühen Phasen, vdf Hochschulverlag AG & Rainer Hampp, Zurich, Stuttgart, pp. 11–25.Google Scholar
Hess, S., Lohmeyer, Q. and Meboldt, M. (2018), “Mobile Eye Tracking in Engineering Design Education”, Design and Technology Education: an International Journal, Vol. 23 No. 2, pp. 86–98.Google Scholar
Jones, G. (2003), “Testing Two Cognitive Theories of Insight”, Journal of Experimental Psychology: Learning, memory and cognition, Vol. 29 No. 5, p. 1017.Google ScholarPubMed
Landis, J.R. and Koch, G.G. (1977), “The measurement of observer agreement for categorical data”, Biometrics, pp. 159–174.10.2307/2529310CrossRefGoogle Scholar
Laukkonen, R.E., Kaveladze, B.T., Tangen, J.M. and Schooler, J.W. (2020), “The dark side of Eureka: Artificially induced Aha moments make facts feel true”, Cognition, Vol. 196, pp. 104–122. 10.1016/j.cognition.2019.104122.10.1016/j.cognition.2019.104122CrossRefGoogle ScholarPubMed
Matthiesen, S. (2011), “Seven years of product development in Industry–experiences and requirements for supporting engineering design with ‘Thinking Tools’”, Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting Society through Engineering Design, Vol. 9: Design Methods and Tools pt. 1, Lyngby/Copenhagen, Denmark, 15.-19.08. 2011.Google Scholar
Matthiesen, S. and Nelius, T. (2018a), “Eye tracking study on successful micro-strategies by design engineers for the synthesis-driven analysis of technical systems”, in Horváth, I., Suárez Rivero, J.P. and Hernández Castellano, P.M. (Eds.), Proceedings of TMCE 2018, 7-11 May, 2018, Las Palmas de Gran Canaria, Gran Canaria, Spain, TU Delft, Delft, 295–303.Google Scholar
Matthiesen, S. and Nelius, T. (2018b), “Managing Assumptions during Analysis - Study on successful Approaches of Design Engineers”, in Ekströmer, P., Schütte, S. and Ölvander, J. (Eds.), DS 91: Proceedings of NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018, The Design Society, Glasgow.Google Scholar
Matthiesen, S., Nelius, T., Pflegler, B. and Gutmann, T. (2017), “Studiendesign zur Untersuchung der synthesegetriebenen Analyse von Konstrukteuren”, DFX-Symposium, Bamberg.Google Scholar
McHugh, M.L. (2012), “Interrater reliability: the kappa statistic”, Biochemia medica: Biochemia medica, Vol. 22 No. 3, pp. 276–282.10.11613/BM.2012.031CrossRefGoogle ScholarPubMed
Meboldt, M., Matthiesen, S. and Lohmeyer, Q. (2013), “The Dilemma of Managing Iterations in Time-to-market Development Processes”, Second International Workshop on the Modelling and Management of Engineering Processes (MMEP 2012). 10.3929/ETHZ-A-009774163.Google Scholar
Nelius, T., Doellken, M., Zimmerer, C. and Matthiesen, S. (2020), “The impact of confirmation bias on reasoning and visual attention during analysis in engineering design: An eye tracking study”, Design Studies, Vol. 71. 10.1016/j.destud.2020.100963.10.1016/j.destud.2020.100963CrossRefGoogle Scholar
Ruckpaul, A., Nelius, T. and Matthiesen, S. (2015), “Differences in analysis and interpretation of technical systems by expert and novice engineering designers”, Proceedings of the 20th International Conference on Engineering Design, Vol. 20, pp. 339–348.Google Scholar
Salvi, C., Bricolo, E., Kounios, J., Bowden, E. and Beeman, M. (2016), “Insight solutions are correct more often than analytic solutions”, Thinking & Reasoning, Vol. 22 No. 4, pp. 443–460. 10.1080/13546783.2016.1141798.10.1080/13546783.2016.1141798CrossRefGoogle ScholarPubMed
Salvi, C., Simoncini, C., Grafman, J. and Beeman, M. (2020), “Oculometric signature of switch into awareness? Pupil size predicts sudden insight whereas microsaccades problem-solving via analysis”, NeuroImage, pp. 116–933. 10.1016/j.neuroimage.2020.116933.Google Scholar
Wynn, D.C. and Eckert, C.M. (2017), “Perspectives on iteration in design and development”, Research in Engineering Design, Vol. 28 No. 2, pp. 153–184. 10.1007/s00163-016-0226-3.10.1007/s00163-016-0226-3CrossRefGoogle Scholar