Universal Access in the Information Society

, Volume 12, Issue 3, pp 279–296 | Cite as

Investigating designers’ and users’ cognitive representations of products to assist inclusive interaction design

  • Anna Mieczakowski
  • Patrick Langdon
  • P. John Clarkson
Long paper


There is strong evidence of the importance of good interaction design in the creation of intuitive-use products. However, there is also a strong indication, both in the literature and in the study with designers documented in this paper, that despite this evidence designers get little support in adequately representing, analysing and comparing design and user information. Since designers require a practical and relatively easy-to-use support tool that would enable them to better understand cognitive processes of users and evaluate the accessibility and usability of different product features, this paper proposes the Goals-Actions-Beliefs-Objects (GABO) modelling approach that can form the basis of such a tool for designers. The four distinct stages of the GABO approach are designed to assess and compare designers and users’ understanding and usage of everyday products. The evaluation results of the GABO approach with eight product designers have indicated that designers find it useful and effective in identifying the key similarities and differences in the understanding of designers and users.


Inclusive design Mental models Product design Cognition Prior experience Approach to modelling user understanding 


  1. 1.
    Anderson, J.R.: Rules of the Mind. Lawrence Erlbaum Associates, Hillsdale (1993)Google Scholar
  2. 2.
    Andreasen, M.M.: Modelling—the language of the designer. J. Eng. Des. 5(2), 103–115 (1994)CrossRefGoogle Scholar
  3. 3.
    Aurisicchio, M., Bracewell, R.H.: Engineering design by integrated diagrams. In: International Conference on Engineering Design, Stanford, California, pp. 301–312 (2009)Google Scholar
  4. 4.
    Benktzon, M.: Designing for our future selves: the Swedish experience. Appl. Ergonom. 24(1), 19–27 (1993)CrossRefGoogle Scholar
  5. 5.
    Bibby, P.A.: Distributed knowledge: in the head, in the world and in the interaction? In: Rogers, Y., Rutherford, A., Bibby, P.A. (eds.) Models in the Mind: Theory, Perspective and Application, pp. 93–99. Academic Press, London (1992)Google Scholar
  6. 6.
    Blackler, A.: Intuitive Interaction with Complex Artefacts. PhD thesis. School of Design, Queensland University of Technology, Australia (2006)Google Scholar
  7. 7.
    Blessing, L., Chakrabarti, A., Wallace, K.A.: Design research methodology. In: International Conference on Engineering Design, Prague, Czech Republic, pp. 50–55 (1995)Google Scholar
  8. 8.
    Browning, T.R.: Applying the design structure matrix to system decomposition and integration problems: a review and new directions. IEEE Trans. Eng. Manage. 48(3), 292–306 (2001)CrossRefGoogle Scholar
  9. 9.
    Bubb, H., Fritzsche, F.: A scientific perspective of digital human models: past, present, and future. In: Duffy, V.G. (ed.) Handbook of Digital Human Modeling: Research for Applied Ergonomics and Human Factors Engineering, pp. 3-1–3-30. Taylor & Francis, Boca Raton (2009)Google Scholar
  10. 10.
    Card, S., Moran, T.P., Newell, A.: The psychology of human-computer interaction. Lawrence Erlbaum Associates, Hillsdale (1983)Google Scholar
  11. 11.
    Cardoso, C., Keates, S., Clarkson, P.J.: Comparing product assessment methods for inclusive design. In: Keates, S., Clarkson, P.J., Langdon, P., Robinson, P. (eds.) Designing a More Inclusive World, pp. 31–40. Springer, London (2004)CrossRefGoogle Scholar
  12. 12.
    Carley, K., Palmquist, M.: Extracting, representing and analysing mental models. Soc. Forces 70(3), 601–636 (1992)Google Scholar
  13. 13.
    Carroll, J.M., Campbell, R.L.: Artifacts as psychological theories: the case of human-computer interaction. Behaviour & Information Technology 8, 247–256 (1989)CrossRefGoogle Scholar
  14. 14.
    Carroll, J.M., Reitman Olson, J.: Mental models in human-computer interaction: research issues about what the user of software knows. National Academy Press, Washington, DC (1987)Google Scholar
  15. 15.
    Carroll, J.M., Carrithers, C.: Blocking learner error states in a training-wheels system. Hum. Factors 26(4), 377–389 (1984)Google Scholar
  16. 16.
    Case, K., Porter, J.M., Gyi, D.E., Marshall, R., Oliver, R.E.: Virtual fitting trials in ‘design for all’. J. Mater. Process. Technol. 1171, 255–261 (2001)CrossRefGoogle Scholar
  17. 17.
    Chayutsahakij, P.: Human Centered Design Innovation. Report, Institute of Design, IIT Technology (2000)Google Scholar
  18. 18.
    Coleman, R., Topalian, A., Dong, H., Clarkson, J.: The business case. In: Coleman, R., Clarkson, J., Dong, H., Cassim, J. (eds.) Design for Inclusivity: A Practical Guide to Accessible, Innovative and User-centred Design, pp. 33–55. Gower Publishing Limited, Aldershot (2007)Google Scholar
  19. 19.
    Cooper, A.: The inmates are running the asylum. SAMS Publishing, Indianapolis (1999)Google Scholar
  20. 20.
    Craik, K.J.W.: The Nature of Explanation. Cambridge University Press, Cambridge (1943)Google Scholar
  21. 21.
    Crilly, N., Blackwell, A.F., Clarkson, P.J.: Using research diagrams for member validation in qualitative research. In: Diagrammatic Representation and Inference International Conference. Stanford, California, pp. 258–262 (2006)Google Scholar
  22. 22.
    Cross, N.: Engineering design methods. Wiley, Chichester (1989)Google Scholar
  23. 23.
    diSessa, A.: Models of computation. In: Norman, D.A., Draper, S.W. (eds.) User-centered System Design: New Perspectives in Human-Computer Interaction, pp. 201–218. Lawrence Erlbaum Associates, Hillsdale (1986)Google Scholar
  24. 24.
    Docampo-Rama, M.: Technology Generations Handling Complex User Interfaces. PhD thesis, Eindhoven University of Technology, The Netherlands (2001)Google Scholar
  25. 25.
    Dong, H.: Barriers to Inclusive Design in the UK. PhD thesis, University of Cambridge, UK (2005)Google Scholar
  26. 26.
    Duffy, V.G.: Handbook of Digital Human Modeling: Research for Applied Ergonomics and Human Factors Engineering. Taylor & Francis, Boca Raton (2009)Google Scholar
  27. 27.
    Eckert, C., Clarkson, P.J., Stacey, M.K.: The spiral of applied research: a methodological view on integrated design research. In: International Conference on Engineering Design, Stockholm, Sweden, pp. 245–246 (2003)Google Scholar
  28. 28.
    Fielding, N., Thomas, H.: Qualitative interviewing. In: Gilbert, N. (ed.) Researching Social Life, pp. 123–144. Sage, London (2001)Google Scholar
  29. 29.
    Freudenthal, A.: The Design of Home Appliances for Young and Old Consumers. PhD thesis, Delft University Press, The Netherlands (1999)Google Scholar
  30. 30.
    Gentner, D., Stevens, A.L.: Mental Models. Lawrence Erlbaum Associates, Hillsdale (1983)Google Scholar
  31. 31.
    Goldsmith, T.E., Davenport, D.M.: Assessing structural similarity of graphs. In: Schvaneveldt, R.W. (ed.) Pathfinder Associative Networks, pp. 31–52. Ablex Publishing Corporation, Norwood (1990)Google Scholar
  32. 32.
    Goodman-Deane, J., Langdon, P., Clarkson, P.J.: Key influences on the user-centred design process. J. Eng. Des. 21, 345–373 (2010)CrossRefGoogle Scholar
  33. 33.
    Gorsuch, R.L.: Factor Analysis, 2nd edn. Erlbaum, Hillsdale (1999)Google Scholar
  34. 34.
    Gulliksen, J., Goransson, B., Boivie, I., Blomkvist, S., Persson, J., Cajander, A.: Key principles for user-centered systems design. Behav. Inf. Technol. 22, 397–409 (2003)CrossRefGoogle Scholar
  35. 35.
    Harvey, L., Anderson, J.: Transfer of declarative knowledge in complex information-processing domains. Hum. Comput. Interact. 11, 69–96 (1996)CrossRefGoogle Scholar
  36. 36.
    Hewer, S., James, L.: Realising potential: two complementary views from the RSA, London. In: Placencia-Porrero, I., Ballabio, E. (eds.) Improving the Quality of Life for the European Citizen: Technology for the Inclusive Design and Equality. IOS Press, London (1998)Google Scholar
  37. 37.
    Hiltz, K., Back, J., Blandford, A.: The roles of conceptual device models and user goals in avoiding device initialization errors. Interact. Comput. 22, 363–374 (2010)CrossRefGoogle Scholar
  38. 38.
    Hosking, I.M., Waller, S.D., Clarkson, P.J.: It is normal to be different: applying inclusive design in industry. Interact. Comput. 22(6), 496–501 (2010)CrossRefGoogle Scholar
  39. 39.
    Hurtienne, J., Blessing, L.: Metaphors as tools for intuitive interaction with technology. 12, 21–52 (2007)Google Scholar
  40. 40.
    Johnson, M.: Moral Imagination. University of Chicago Press, Chicago (1993)Google Scholar
  41. 41.
    Johnson, P., Johnson, H., Waddington, R., Shouls, A.: Task-related knowledge structures: analysis, modeling and application. In: Jones, D.M., Winder, R. (eds.) People and Computers: From Research to Implementation, pp. 35–62. Cambridge University Press, Cambridge (1988)Google Scholar
  42. 42.
    Johnson-Laird, P.N.: Mental Models. Harvard University Press, Cambridge (1983)Google Scholar
  43. 43.
    Jordan, P.W.: Designing Pleasurable Products: An Introduction to the New Human Factors. Taylor & Francis, London (2000)CrossRefGoogle Scholar
  44. 44.
    Keates, S., Clarkson, P.J.: Countering Design Exclusion: An Introduction to Inclusive Design. Springer, London (2004)CrossRefGoogle Scholar
  45. 45.
    Kieras, D.E.: What mental model should be taught: choosing instructional content for complex engineered systems. In: Psotka, J., Massey, L.D., Mutter, S.A. (eds.) Intelligent Tutoring Systems: Lessons Learned, pp. 85–111. Lawrence Erlbaum Associates, Hillsdale (1988)Google Scholar
  46. 46.
    Kirwan, B., Ainsworth, L.K.: A Guide to Task Analysis: The Task Analysis Working Group. Taylor & Francis, London (1992)Google Scholar
  47. 47.
    Klimoski, R., Mohammed, S.: Team mental model: construct or metaphor? J. Manage. 20(2), 403–437 (1994)Google Scholar
  48. 48.
    Kolbitsch, J., Maurer, H.: Transclusions in an HTML-based environment. J. Comput. Inf. Technol. 14(2), 161–173 (2006)Google Scholar
  49. 49.
    Kotler, P., Rath, G.A.: Design: a powerful but neglected strategic tool. J. Bus. Strategy 5, 16–21 (1984)CrossRefGoogle Scholar
  50. 50.
    Kouprie, M., Sleeswijk Visser, F.: A framework for empathy in design: stepping into and out of the user’s life. J. Eng. Des. 20(5), 437–448 (2009)CrossRefGoogle Scholar
  51. 51.
    Laird, J.E., Newell, A., Rosenbloom, P.S.: SOAR: an architecture for general intelligence. Artif. Intell. 33, 1–64 (1987)CrossRefGoogle Scholar
  52. 52.
    Langdon, P., Thimbleby, H.: Inclusion and interaction: designing interaction for inclusive populations (editorial). Interact. Comput. 22(6), 439–448 (2010)CrossRefGoogle Scholar
  53. 53.
    Langdon, P.M., Lewis, T., Clarkson, P.J.: Prior experience in the use of domestic product interfaces. Univ. Access Inf. Soc. 9, 209–225 (2009)CrossRefGoogle Scholar
  54. 54.
    Langdon, P.M., Lewis, T., Clarkson, P.J.: The effects of prior experience on the use of consumer products. Univ. Access Inf. Soc. 6, 179–191 (2007). Special Issue on Designing Accessible TechnologyCrossRefGoogle Scholar
  55. 55.
    Larkin, J.H., Simon, H.A.: Why a diagram is (sometimes) worth ten thousand words. Cogn. Sci. 11(1), 65–100 (1987)CrossRefGoogle Scholar
  56. 56.
    Liddle, D.: Design of the conceptual model. In: Winograd, T. (ed.) Bringing Design to Software, pp. 17–31. Addison-Wesley, Reading (1996)Google Scholar
  57. 57.
    Lim, C.S.C.: Designing inclusive ICT products for older users: taking into account the technology generation effect. J. Eng. Des. 21(2–3), 189–206 (2010)CrossRefGoogle Scholar
  58. 58.
    MacLean, A., Young, R.M., Bellotti, V.M.E., Moran, T.P.: Questions, options, and criteria: elements of design space analysis. Hum. Comput. Interact. 6(3–4), 201–250 (1991)CrossRefGoogle Scholar
  59. 59.
    Mark, M.A., Greer, J.E.: The VCR tutor: effective instruction for device operation. J. Learn. Sci. 4, 209–246 (1995)CrossRefGoogle Scholar
  60. 60.
    Mattelmäki, T., Battarbee, K.: Empathy probes. In: Participatory Design Conference, Palo Alto, California, pp. 266–271 (2002)Google Scholar
  61. 61.
    Mieczakowski, A., Langdon, P., Clarkson, P.J.: Specifying an inclusive model of product-user interaction. In: International Conference on Engineering Design, Stanford, California, pp. 143–154 (2009)Google Scholar
  62. 62.
    Mossink, J.C.M.: Evaluation of design practice and the implementation of ergonomics. Ergonomics 33(5), 613–619 (1990)CrossRefGoogle Scholar
  63. 63.
    Norman, D.A.: Some observations on mental models. In: Gentner, D., Stevens, A.L. (eds.) Mental Models, pp. 7–14. Lawrence Erlbaum Associates, Hillsdale (1983)Google Scholar
  64. 64.
    Norman, D.A.: The Design of Everyday Things. Basic Books, London (2002)Google Scholar
  65. 65.
    Otto, K., Wood, K.: Product Design: Techniques in Reverse Engineering, Systematic Design, and New Product Development. Prentice-Hall, New York (2001)Google Scholar
  66. 66.
    Payne, S.J.: Mental models in human-computer interaction. In: Jacko, J.A., Sears, A. (eds.) The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications, pp. 63–76. Taylor & Francis, New York (2008)Google Scholar
  67. 67.
    Persad, U., Langdon, P., Clarkson, P.J.: Characterising user capabilities to support inclusive design evaluation. Univ. Access Inf. Soc. 6, 119–135 (2007). Special Issue on Designing Accessible TechnologyCrossRefGoogle Scholar
  68. 68.
    Popovic, V.: Activity and designing pleasurable interaction with everyday products. In: Green, W. (ed.) Pleasure with Products: Beyond Usability, pp. 367–375. Taylor & Francis, London (2002)Google Scholar
  69. 69.
    Porter, J.M., Case, K., Marshall, R., Gyi, D., Oliver, R.E.: Beyond Jack and Jill: designing for individuals using HADRIAN. Int. J. Ind. Ergon. 33, 249–264 (2004)CrossRefGoogle Scholar
  70. 70.
    Preece, J., Rogers, Y., Sharp, H.: Interaction Design: Beyond Human-Computer Interaction. Wiley, New York (2002)Google Scholar
  71. 71.
    Rasmussen, J.: Skills, rules, and knowledge: signals, signs, and symbols, and other distinctions in human performance models. IEEE Trans. Syst. Man Cybern. 13, 257–266 (1983)CrossRefGoogle Scholar
  72. 72.
    Rasmussen, J., Pejtersen, A., Goodstein, L.P.: Cognitive Systems Engineering. Wiley, New York (1994)Google Scholar
  73. 73.
    Reason, J.T.: Human Error. Cambridge University Press, Cambridge (1990)CrossRefGoogle Scholar
  74. 74.
    Ricability: Inclusive design: products that are easy for everyone to use. Disability Rights Commission, DRC/TP/IC (2001)Google Scholar
  75. 75.
    Rogers, Y.: Mental models and complex tasks. In: Rogers, Y., Rutherford, A., Bibby, P.A. (eds.) Models in the Mind: Theory, Perspective and Application, pp. 145–149. Academic Press, London (1992)Google Scholar
  76. 76.
    Rutherford, A., Wilson, J.R.: Models of mental models: an ergonomist-psychologist dialogue. In: Trauber, M.J., Ackermann, D. (eds.) Mental Models and Human-Computer Interaction 2, pp. 39–58. Elsevier Science Publishers, Amsterdam (1991)Google Scholar
  77. 77.
    Ryu, H., Monk, A.: Analysing interaction problems with cyclic interaction theory: low-level interaction walkthrough. Psychol. J. 2(3), 304–330 (2004)Google Scholar
  78. 78.
    Salustri, F.A., Weerasinghe, J.S., Bracewell, R.H., Eng, N.: Visualizing early engineering design information with diagrams. J. Des. Res. 6, 190–217 (2007)Google Scholar
  79. 79.
    Shneiderman, B.: Promoting universal usability with multi-layer interface design. In: Conferences on Universal Usability, New York (2003)Google Scholar
  80. 80.
    Stanton, N.A., Baber, C.: Validating task analysis for error identification: reliability and validity of a human error prediction technique. Ergonomics 48(9), 1097–1113 (2005)CrossRefGoogle Scholar
  81. 81.
    Stanton, N., Hedge, A., Brookhuis, K., Salas, E., Hendrick, H.: Handbook of Human Factors and Ergonomics Methods. CRC Press, Boca Raton (2005)Google Scholar
  82. 82.
    Thomas, D.R.: A general inductive approach for analysing qualitative evaluation data. Am. J. Eval. 27, 237–246 (2006)CrossRefGoogle Scholar
  83. 83.
    Ulwick, A.W.: Turn customer input into innovation. Harvard Business Review 80, 91–97 (2002)Google Scholar
  84. 84.
    van Engers, T.: Knowledge Management: The Role of Mental Models in Business System Design. PhD thesis, Departmennt of Computer Science, Vrije Universiteit (2001)Google Scholar
  85. 85.
    van Kleef, E., van Trijp, H., Luning, P.: Consumer research in the early stages of new product development: a critical review of methods and techniques. Food Qual. Prefer. 16, 181–201 (2004)CrossRefGoogle Scholar
  86. 86.
    Waller, S.D., Williams, E.Y., Langdon, P.M., Clarkson, P.J.: Quantifying exclusion for tasks related to product interaction. In: Landgon, P., Clarkson, J., Robinson, P. (eds.) Designing Inclusive Interactions, pp. 57–69. Springer, London (2010)CrossRefGoogle Scholar
  87. 87.
    Werhane, P.H.: Moral imagination and systems thinking. J. Bus. Ethics 38, 33–42 (2002)CrossRefGoogle Scholar
  88. 88.
    Yang, M.C., Epstein, D.J.: Study of prototypes, design activity and design outcome. Des. Stud. 26(6), 649–669 (2005)CrossRefGoogle Scholar
  89. 89.
    Young, R.M.: Surrogates and mappings: two kinds of conceptual models for interactive devices. In: Gentner, D., Stevens, A.L. (eds.) Mental Models, pp. 35–52. Lawrence Erlbaum Associates, Hillsdale (1983)Google Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Anna Mieczakowski
    • 1
  • Patrick Langdon
    • 1
  • P. John Clarkson
    • 1
  1. 1.Department of Engineering, Engineering Design CentreUniversity of CambridgeCambridgeUK

Personalised recommendations