Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-25T16:38:33.513Z Has data issue: false hasContentIssue false
  • English
  • Français

Addressing Cognitive Challenges in Design – A Review on Existing Approaches

Part of: Methods of Design Research

Published online by Cambridge University Press:  26 July 2019

Weining Ning ,
Joy Goodman-Deane  and
P. John Clarkson

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.

Insufficient design often causes challenges to users on a cognitive level, hindering them from interacting with products smoothly. There is a lack of effective design tools and supporting materials that can help designers to understand human cognition and how it affects the way that users experience and use products and services. This paper aims to identify current approaches that can be applied to address this issue, and to examine their strengths and weaknesses. This helps to identify future directions for developing and improving cognitive design supports. A literature review was conducted of research publications in the fields of both design and cognition. Four key approaches are identified: cognitive design principles/guidelines, the demand-capability approach, cognitive walkthrough and cognitive modelling. Their strengths and weaknesses are analyzed from a design standpoint. The paper also analyses the underlying causes of the insufficient uptake of cognitive design approaches by designers.

Keywords

Cognitive challengeInclusive designUser centred designDesign methods
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2775 - 2784
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

Abascal, J. and Nicolle, C. (2005), “Moving towards inclusive design guidelines for socially and ethically aware HCI”, Interacting with Computers, Vol. 17 No. 5, pp. 484–505. http://doi.org/10.1016/j.intcom.2005.03.002.Google Scholar
Altay, B. (2017), “Multisensory Inclusive Design Education: A 3D Experience”, The Design Journal, Vol. 20 No. 6, pp. 821–846. http://doi.org/10.1080/14606925.2017.1371949.Google Scholar
Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., Lebiere, C. and Qin, Y. (2004), “An integrated theory of the mind”, Psychological review, Vol. 111 No. 4, p. 1036. http://doi.org/10.1037/0033-295X.111.4.1036.Google Scholar
Bastien, J.M.C. and Scapin, D.L. (1992), “A validation of ergonomic criteria for the evaluation of human-computer interfaces”, International Journal of Human-Computer Interaction, Vol. 4 No. 2, pp. 183–196. http://doi.org/10.1080/10447319209526035.Google Scholar
Bastien, J.M.C. and Scapin, D.L. (1995), “How usable are usability principles, criteria and standards?” in: Advances in Human Factors/Ergonomics Elsevier, pp. 343–348.https://doi.org/10.1016/S0921-2647(06)80240-6Google Scholar
Blair-Early, A. and Zender, M. (2008), “User interface design principles for interaction design”, Design Issues, Vol. 24 No. 3, pp. 85–107. http://doi.org/10.1162/desi.2008.24.3.85.Google Scholar
Blessing, L.T. and Chakrabarti, A. (2009), DRM, a design research methodology, Springer Science & Business Media. https://doi.org/10.1007/978-1-84882-587-1_2Google Scholar
BSI (2005), BS 7000-6:2005 Design management systems, British Standards Institute, LodonGoogle Scholar
Butterfield, A. and Ngondi, G.E. (2016), A dictionary of computer science, Seventh ed., Oxford University Press. http://doi.org/10.1093/acref/9780199688975.001.0001Google Scholar
Card, S.K., Newell, A. and Moran, T.P. (1983), The Psychology of Human-Computer Interaction, L. Erlbaum Associates Inc. https://doi.org/10.1201%2F9780203736166Google Scholar
Chittaro, L. and De Marco, L. (2004), “Driver distraction caused by mobile devices: studying and reducing safety risks”, in 1st Int'l workshop mobile technologies and health: Benefits and Risks, pp. 1–19.Google Scholar
Clarkson, P.J., Waller, S. and Cardoso, C. (2015), “Approaches to estimating user exclusion”, Applied Ergonomics, Vol. 46 Part B, pp. 304–310. http://doi.org/10.1016/j.apergo.2013.03.001.Google Scholar
Czerwinski, M.P. and Larson, K. (2002), “Cognition and the Web: moving from theory to Web design” in: Ratner, J. (Ed). Human Factors and Web Development, Second ed., Erlbaum, Boca Raton, NJ. http://doi.org/10.1201/b12467Google Scholar
Darses, F. and Wolff, M. (2006), “How do designers represent to themselves the users’ needs?”, Applied Ergonomics, Vol. 37 No. 6, pp. 757–764. http://doi.org/10.1016/j.apergo.2005.11.004.Google Scholar
EDC (2018), Exclusion Calculator Inclusive Design Toolkit, available: http://calc.inclusivedesigntoolkit.com/ [accessed 19 July].Google Scholar
Fichter, D. (2004), “Heuristic and cognitive walk-through evaluations”, Online, Vol. 28 No. 3, pp. 53–56.Google Scholar
Frøkjær, E. and Hornbæk, K. (2008), “Metaphors of human thinking for usability inspection and design”, ACM Transactions on Computer-Human Interaction (TOCHI), Vol. 14 No. 4, p. 20. http://doi.org//10.1145%2F1314683.1314688.Google Scholar
Gersh, J.R., McKneely, J.A. and Remington, R.W. (2005), “Cognitive engineering: Understanding human interaction with complex systems”, Johns Hopkins APL technical digest, Vol. 26 No. 4, pp. 377–382.Google Scholar
Goodman-Deane, J., Waller, S.D., Williams, E.Y., Langdon, P.M. and Clarkson, P.J. (2011), “Estimating exclusion: a tool to help designers”, in Include 2011, London, 18-20 April 2011, Royal College of Art.Google Scholar
Grudin, J. (2012), “A Moving Target: The Evolution of Human-Computer Interaction Introduction” in: Jacko, J. A. (Ed). Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications, Third ed. CRC Press pp. xxvii–lxiGoogle Scholar
John, B.E. and Packer, H. (1995), “Learning and using the cognitive walkthrough method: a case study approach”, in Proceedings of the SIGCHI conference on Human factors in computing systems, ACM Press/Addison-Wesley Publishing Co., pp. 429–436, available: http://doi.org//10.1145/223904.223962.Google Scholar
John, B.E., Prevas, K., Salvucci, D.D. and Koedinger, K. (2004), “Predictive human performance modeling made easy”, in Proceedings of the SIGCHI conference on Human factors in computing systems, ACM, pp. 455–462, available: http://doi.org/10.1145/985692.985750.Google Scholar
Johnson, J. (2013), Designing with the mind in mind: simple guide to understanding user interface design guidelines, Elsevier. https://doi.org/10.1016/B978-0-12-407914-4.00001-4Google Scholar
Kalyuga, S., Plass, J.L., Moreno, R. and Brunken, R. (2010), “Schema Acquisition and Sources of Cognitive Load” in: Plass, J. L., Brünken, R. and Moreno, R., eds., Cognitive Load Theory, Cambridge University Press, Cambridge, pp. 48–64. http://doi.org/10.1017/cbo9780511844744.005Google Scholar
Laird, J.E., Newell, A. and Rosenbloom, P.S. (1987), “Soar: An architecture for general intelligence”, Artificial intelligence, Vol. 33 No. 1, pp. 1–64. http://doi.org//10.1016/0004-3702(87)90050-6.Google Scholar
Langdon, P. and Thimbleby, H. (2010), “Inclusion and interaction: Designing interaction for inclusive populations”, Interacting with Computers, Vol. 22 No. 6, pp. 439–448. http://doi.org/10.1016/j.intcom.2010.08.007.Google Scholar
Li, X.Y. and Gunal, M. (2012), “Exploring cognitive modelling in engineering usability design”, Journal of Engineering Design, Vol. 23 No. 1-3, pp. 77–97. http://doi.org/10.1080/09544828.2010.528379.Google Scholar
Liyanage, C., Elhag, T., Ballal, T. and Li, Q. (2009), “Knowledge communication and translation–a knowledge transfer model”, Journal of Knowledge management, Vol. 13 No. 3, pp. 118–131. http://doi.org//10.1108/13673270910962914.Google Scholar
Maguire, M. (2001), “Methods to support human-centred design”, International Journal of Human-Computer Studies, Vol. 55 No. 4, pp. 587–634. http://doi.org//10.1006/ijhc.2001.0503.Google Scholar
Mahatody, T., Sagar, M. and Kolski, C. (2010), “State of the Art on the Cognitive Walkthrough Method, Its Variants and Evolutions”, International Journal of Human-Computer Interaction, Vol. 26 No. 8, pp. 741–785. http://doi.org/92478501210.1080/10447311003781409.Google Scholar
Mayer, R.E. and Moreno, R. (2002), “Aids to computer-based multimedia learning”, Learning and Instruction, Vol. 12 No. 1, pp. 107–119. http://doi.org/10.1016/S0959-4752(01)00018-4.Google Scholar
McGinley, C. and Dong, H. (2015), “Designing with Information and Empathy: Delivering Human Information to Designers”, The Design Journal, Vol. 14 No. 2, pp. 187–206. http://doi.org/10.2752/175630611x12984592780005.Google Scholar
Mieczakowski, A., Langdon, P. and Clarkson, P.J. (2012), “Investigating designers’ and users’ cognitive representations of products to assist inclusive interaction design”, Universal Access in the Information Society, Vol. 12 No. 3, pp. 279–296. http://doi.org/10.1007/s10209-012-0278-8.Google Scholar
Nickpour, F. and Dong, H. (2015), “Designing Anthropometrics! Requirements Capture for Physical Ergonomic Data for Designers”, The Design Journal, Vol. 14 No. 1, pp. 92–111. http://doi.org/10.2752/175630610x12877385838849.Google Scholar
O'Hare, D., Wiggins, M., Williams, A. and Wong, W. (2014), “Cognitive task analyses for decision centred design and training” in: Task analysis, CRC Press, pp. 176–196Google Scholar
Olson, G.M. and Olson, J.S. (2003), “Human-computer interaction: Psychological aspects of the human use of computing”, Annual review of psychology, Vol. 54 No. 1, pp. 491–516. http://doi.org/10.1146/annurev.psych.54.101601.145044.Google Scholar
Oygür, I. (2017), “User, Research, and Practice. Learning from Design Consultancies”, The Design Journal, Vol. 20 No. sup1, pp. S4621–S4631. http://doi.org/10.1080/14606925.2017.1352959.Google Scholar
Peacock, B. and Resnick, M. (2011), “The Six Us: An Ergonomics Approach to Enhancing Product and Process Evaluations”, Ergonomics in Design, Vol. 19 No. 2, pp. 25–29. http://doi.org/10.1177/1064804611408016.Google Scholar
Ritter, F.E., Baxter, G.D., Jones, G. and Young, R.M. (2001), “User interface evaluation: How cognitive models can help” in: Carroll, J. M. (Ed). Hu6man-computer interaction in the new millennium, pp. 125–147. https://doi.org/10.1145/638574.638592Google Scholar
Rosson, M.B., Maass, S. and Kellogg, W.A. (1987), “Designing for designers: an analysis of design practice in the real world”, in CHI ‘87 Proceedings of the SIGCHI/GI Conference on Human Factors in Computing Systems and Graphics Interface, Toronto, Ontario, Canada http://doi.org/10.1145/29933.30873, ACM, pp. 137–142 available: http://doi.org/10.1145/29933.30873.Google Scholar
Salvucci, D.D. and Lee, F.J. (2003), “Simple cognitive modeling in a complex cognitive architecture”, in Proceedings of the SIGCHI conference on Human factors in computing systems, ACM, pp. 265–272, available: http://doi.org//10.1145/642611.642658Google Scholar
Schønheyder, J.F. and Nordby, K. (2018), “The use and evolution of design methods in professional design practice”, Design Studies, Vol. 58, pp. 36–62. http://doi.org//10.1016/j.destud.2018.04.001.Google Scholar
Shankar, A., Lin, H., Brown, H.-F. and Rice, C. (2015), “Rapid Usability Assessment of an Enterprise Application in an Agile Environment with CogTool”, in Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, ACM, Seoul, Republic of Korea, pp. 719–726, available: http://doi.org//10.1145/2702613.2702960.Google Scholar
Tarpin-Bernard, F. and Habieb-Mammar, H. (2005), “Modeling elementary cognitive abilities for adaptive hypermedia presentation”, User Modeling and User-Adapted Interaction, Vol. 15 No. 5, pp. 459–495. http://doi.org/10.1007/s11257-005-2529-3.Google Scholar
Tenneti, R., Goodman-Deane, J., Langdon, P., Waller, S., Ruggeri, K., Clarkson, P.J. and Huppert, F.A. (2013), “Design and delivery of a national pilot survey of capabilities”, International Journal of Human Factors and Ergonomics, Vol. 2 No. 4, pp. 281–305. http://doi.org//10.1504/ijhfe.2013.059375Google Scholar
Thagard, P. (2017), “Cognitive Science” in: Frodeman, R. (Ed). The Oxford Handbook of Interdisciplinarity, 2 ed. Oxford University Press. http://doi.org/10.1093/oxfordhb/9780198733522.001.0001Google Scholar
Van Biljon, J. and Renaud, K. (2016), “Validating mobile phone design guidelines: Focusing on the elderly in a developing country”, in Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists, ACM, p. 44.Google Scholar
West, R.L. and Emond, B. (2002), “Can cognitive modeling improve rapid prototyping”, in Altmann, Erik M., Schunn, A. C., Christian, D., Gray, Wayne D., ed., Proceedings of the Fourth International Conference on Cognitive Modeling, New York, pp. 271–273, available: http://doi.org//10.4324/9781410605979Google Scholar
Wilson, C. (2014), “Cognitive Walkthrough” in: Wilson, C. (Ed). User Interface Inspection Methods, Morgan Kaufmann, Boston, pp. 65–79. http://doi.org/10.1016/b978-0-12-410391-7.00004-xGoogle Scholar
Wong, T.J., Cokely, E.T. and Schooler, L.J. (2010), “An online database of ACT-R parameters: Towards a transparent community-based approach to model development”, in Proceedings of the 10th international conference on cognitive modeling, Citeseer, pp. 282–286.Google Scholar
Zaphiris, P., Kurniawan, S. and Ghiawadwala, M. (2006), “A systematic approach to the development of research-based web design guidelines for older people”, Universal Access in the Information Society, Vol. 6 No. 1, pp. 59–75. http://doi.org/10.1007/s10209-006-0054-8.Google Scholar