Skip to main content
Log in

Hierarchical thinking: a cognitive tool for guiding coherent decision making in design problem solving

  • Published:
International Journal of Technology and Design Education Aims and scope Submit manuscript

Abstract

This paper builds on two concepts, the first of which is the extended information processing model of expert design cognition. This proposes twelve internal psychological characteristics interacting with the external world of expert designers during the early phases of the design process. Here, I explore one of the characteristics, hierarchical abstraction, and adapt it into an alternative ontological model of decision making. The model serves as an in-depth descriptor of how designers from different domains transform their mental states using judgment and decision making through hierarchical abstraction. The second concept entails an expansion of the idea of synergistic vertical transformation as a framework for mapping expert designers’ design process. Here, I focus on hierarchical decision making as multi-directional, and inter-relating the internal and external world of designers. In doing so, I provide a coding tool for researchers interested in exploring designers’ complex decision making processes. Concurrently, the model serves as decision making tool in design and technology education classrooms. As such, the paper focuses on the ontology of conceptual structures that support the early phases of the design process. This was based on empirical research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Anderson, M. L. (2003). Embodied cognition: A field guide. Artificial Intelligence, 149(1), 91–130.

    Article  Google Scholar 

  • Anthony, W. S. (1973). Learning to discover rules by discovery. Journal of Educational Psychology, 64, 325–328.

    Article  Google Scholar 

  • Basden, A. (2000). The aspectual framework of meaning. Retrieved from The Dooyeweerd Pages website. http://www.dooy.salford.ac.uk/contact.html.

  • Brandstatter, V., Heimbeck, D., Malzacher, J. T., & Frese, M. (2003). Goals need implementation intentions: The model of action phases tested in the applied setting of continuing education. European Journal of Work and Organizational Psychology, 12(1), 37–59.

    Article  Google Scholar 

  • Buzan, T. (2005). Mind map handbook. London: Thorsons.

    Google Scholar 

  • Cascetta, E. (2001). Transportation systems engineering: Theory and methods. Dordrecht: Springer.

    Book  Google Scholar 

  • Collins, A., Brown, J. S., & Newman, S. E. (1987). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematics. Illinois: University of Illinois at Urbana-Champaign.

    Google Scholar 

  • Conlan, T. (2006). Formative assessment of classroom concept maps: The reasonable fallible analyser. Journal of Interactive Learning Research, 17(1), 15–36.

    Google Scholar 

  • Cross, N. (2001). Design cognition: Results from protocol and other empirical studies of design activity. In C. Eastman, M. McCracken, & W. Newstetter (Eds.), Design knowing and learning: Cognition in design education. Oxford: Elsevier.

    Google Scholar 

  • de Miranda, M. A. (2004). The grounding of a discipline: Cognition and instruction in technology education. International Journal of Technology and Design Education, 14, 61–77.

    Article  Google Scholar 

  • de Vries, M. J. (2006). Technological knowledge and artifacts: An analytical view. In J. R. Dakers (Ed.), Defining technological literacy. Towards an epistemological framework. New York: Pelgrave MacMillan.

    Google Scholar 

  • De Vries, M., Custer, R. L., Dakers, J. R., & Martin, G. (2007). Analyzing best practices in technology educatiion. Rotterdam: Sense Publishers.

    Google Scholar 

  • Edelson, D. C., Gordin, D. N., & Pea, R. D. (1999). Addressing the challenges of inquiry-based learning through technology and curriculum design. The Journal of the Learning Sciences, 8(3&4), 391–450.

    Article  Google Scholar 

  • Eder, W. E. (2012). Comparisons of several design theories and methods with the legacy of Vladimir Hubka.

  • Epley, N., & Gilovich, T. (2006). The anchoring-and-adjustment heuristic. Why the adjustments are insufficient. Psychological Science, 17(4), 311–318.

    Article  Google Scholar 

  • Ertmer, P. A., & Newby, T. J. (2013). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 26(2), 43–71.

    Article  Google Scholar 

  • Fox, J., Cooper, R. P., & Glasspool, D. W. (2013). A canonical theory of dynamic decision-making. Frontiers in Psychology, 4(150), 1–19.

    Google Scholar 

  • Gavrilova, T., Leshcheva, I., & Strakhovich, E. (2015). Gestalt principles of creating learning business ontologies for knowledge codification. Knowledge Management Research & Practice, 13(4), 418–428.

    Article  Google Scholar 

  • Gero, J. S., & Kannengieser, U. (2004). The situated function-behaviour-structure framework. Design Studies, 25, 373–391.

    Article  Google Scholar 

  • Gibson, J. J. (1986). The ecological approach to perception. Hillside, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103(4), 650–669.

    Article  Google Scholar 

  • Goel, V. (1995). Sketches of thought. Cambridge: MIT Press.

    Google Scholar 

  • Goldstein, W. M., & Hogarth, R. M. (1997). Judgment and decision research: Some historical context. In W. M. Goldstein & R. M. Hogarth (Eds.), Research on judgment and decision making: Currents, connections and controversies (pp. 3–68). Cambridge: Cambridge University Press.

    Google Scholar 

  • Gollwitzer, P. M., & Schaal, B. (1998). Metacognition in action: The importance of implementation intentions. Personality and Social Psychology Review, 2(2), 124–136.

    Article  Google Scholar 

  • Hastie, R. (2001). Problems for judgment and decision making. Annual Review Psychology, 52, 653–683.

    Article  Google Scholar 

  • Haupt, G. (2013). The cognitive dynamics of socio-technological thinking in the early phases of expert designers’ design process. Unpublished PhD, University of Pretoria, Pretoria.

  • Haupt, G. (2015). Learning from experts: Fostering extended thinking in the early phases of the design process. International Journal of Technology and Design Education, 25(4), 483–520.

    Article  Google Scholar 

  • Hennessy, S. (1993). Situated cognition and cognitive apprenticeship: Implications for classroom learning. Studies in Science Education, 22(1), 1–44.

    Article  Google Scholar 

  • Hofweber, T. (2014). Logic and ontology. In E. N. Zalta (Ed.), The stanford Encyclopedia of philosophy (Vol. Fall 2014 ed.). Stanford: Standford University.

  • Johnson, S. D., & Daugherty, J. (2008). Quality and characteristics of recent research in technology education. Journal of Technology Education, 20(1), 16–31.

    Article  Google Scholar 

  • Jonassen, D. (1998). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional design models and strategies (2nd ed.). Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Katsikopoulos, K. V. (2009). Coherence and correspondence in engineering design: Informing the conversation and connecting with judgment and decision-making research. Judgment and Decision Making, 4(2), 147–153.

    Google Scholar 

  • Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discover, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.

    Article  Google Scholar 

  • Kluge, P., & Malan, D. F. (2011). The application of the analytical hierarchical process in complex mining engineering design problems. The Journal of the South African Institute of Mining and Metallurgy, 111(December), 847–855.

    Google Scholar 

  • Kroes, P. A. (2002). Design methodology and the nature of technical artefacts. Design Studies, 23, 287–302.

    Article  Google Scholar 

  • Kroes, P. A., & Meijers, A. (2002). The dual nature of technical artifacts. Techné, 6(2), 4–8.

  • Lawson, B. (2006). How designers think. Boston: Elsevier.

    Google Scholar 

  • Mitcham, C. (2002). Do artifacts have dual natures? Two points of commentary on the delft project. Techné, 6(2), 93–95.

    Google Scholar 

  • Mitcham, C., & Holbrook, J. B. (2006). Understanding technological design. In J. S. Dakers (Ed.), Defining technological literacy. Towards an epistemological framework. New York: Palgrave MacMillan.

    Google Scholar 

  • Oxman, R. (2002). The thinking eye: Visual re-cognition in design emergence. Design Studies, 23(2), 135–164.

    Article  Google Scholar 

  • Oxman, R. (2004). Think-maps: Teaching design thinking in design education. Design Studies, 25(1), 63–91.

    Article  Google Scholar 

  • Petrina, S. (2007). Advanced teaching methods for the technology classroom. London: Information Science Publishing.

    Book  Google Scholar 

  • Robbins, P. (2009). The Cambridge handbook of situated cognition. Cambridge: Cambridge University Press.

    Google Scholar 

  • Savin-Baden, M. (2007). Challenging PBL models and perspectives. In E. de Graaf & A. Kolmos (Eds.), Management of change: Implementation of problem-based and project-based learning in engineering. Rotterdam: Sense Publishers.

    Google Scholar 

  • Schön, D. (1984). Problems, frames and perspectives on designing. Design Studies, 5(3), 135–156.

    Google Scholar 

  • Seram, N. (2013). Decision making in product development—a review of the literature. International Journal of Engineering and Applied Sciences, 2(4), 1–11.

    Google Scholar 

  • Simon, H. A. (1996). The sciences of the artificial (3rd ed.). Cambridge, MA: MIT Press.

    Google Scholar 

  • Sowa, J. F. (1984). Conceptual structures: Information processing in mind and machine. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Suwa, M., Purcell, T., & Gero, J. (1998). Macroscopic analysis of design processes based on a scheme for coding designers’ cognitive actions. Design Studies, 19(4), 455–483.

    Article  Google Scholar 

  • Suwa, M., & Tversky, B. (1996). What architects see in their design sketches: Implications for design tools. Paper presented at the Human Factors in Computing Systems. ACM, New York.

  • Tversky, A., & Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

    Article  Google Scholar 

  • Tversky, A., & Kahneman, D. (1986). Rational choice and the framing of decisions. The Journal of Business, 59(4), S251–S278.

    Article  Google Scholar 

  • Tversky, A., & Simonson, I. (1993). Context-dependent preferences. Management Science, 39(10), 1179–1189.

    Article  Google Scholar 

  • Verkerk, M. J., Hoogland, J., van der Stoep, J., & de Vries, M. J. (2007). Denken Ontwerpen Maken. Basisboek Techniekfolosofie. Amsterdam: Boom.

    Google Scholar 

  • Wagemans, J., Elder, J. H., Kubovv, M., Palmer, S. E., Peterson, M. A., Singh, M., & van der Heydt, R. (2012). A century of Gestalt psychology in visual perception 1. Perceptual grouping and figure-ground organisation. Psychology Bulletin, 138(6), 1172–1217.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Grietjie Haupt.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Haupt, G. Hierarchical thinking: a cognitive tool for guiding coherent decision making in design problem solving. Int J Technol Des Educ 28, 207–237 (2018). https://doi.org/10.1007/s10798-016-9381-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10798-016-9381-0

Keywords

Navigation