Advertisement

A Combinatory Approach to Assessing User Performance of Digital Interfaces

  • P. K. A. Wollner
  • P. M. Langdon
  • P. J. Clarkson
Conference paper

Abstract

Digital devices are often restricted by the complexity of their user interface (UI) design. While accessibility guidelines exist that reduce the barriers to access information and communications technology (ICT), guidelines alone do not guarantee a fully inclusive design. In the past, iterative design processes using representative user groups to test prototypes were the standard methods for increasing the inclusivity of a given design, but cognitive modelling (the modelling of human behaviour, in this instance when interacting with a device) has recently become a feasible alternative to rigorous user testing (John and Suzuki 2009). Nonetheless, many models are limited to an output that communicates little more than the assumed time the modelled user would require to complete the task given a specific way of doing so (John 2011). This chapter introduces a novel approach that makes use of the overlay of user modelling output (timings) onto a graphical representation of an entire UI, thereby enabling the computation of new metrics that indicate the relative inclusiveness of individual screens of the UI.

References

  1. Anderson JR, Bothell D, Byrne MD, Douglass S, Lebiere C et al (2004) An integrated theory of the mind. Psychol Rev 111:1036–1060CrossRefGoogle Scholar
  2. Biswas P, Robinson P, Langdon PM (2012) Designing inclusive interfaces through user modeling and simulation. Int J Human-Comput Interact 28(1):1–33CrossRefGoogle Scholar
  3. Bondy A, Murty U (2008) Graph theory. In: Graduate texts in mathematics. Springer, New YorkGoogle Scholar
  4. Councill IG, Haynes SR, Ritter FE (2003) Explaining soar: analysis of existing tools and user information requirements. In: Proceedings of the 5th international conference on cognitive modelingGoogle Scholar
  5. John BE (2011) Using predictive human performance models to inspire and support UI design recommendations. In: Proceedings of the ACM CHI conference on human factors in computing systems, Vancouver, CanadaGoogle Scholar
  6. John BE, Prevas K, Salvucci DD, Koedinger K (2004) Predictive human performance modeling made easy. In: Proceedings of the SIGCHI conference on human factors in computing systems, New York, NY, USGoogle Scholar
  7. John BE, Suzuki S (2009) Toward cognitive modeling for predicting usability. In: Human-computer interaction. New trends. Lecture notes in computer science, vol 5610, pp 267–276Google Scholar
  8. Langdon PM, Persad U, Clarkson PJ (2010) Developing a model of cognitive interaction for analytical inclusive design evaluation. Interact Comput 22(6):510–529CrossRefGoogle Scholar
  9. Langdon PM, Thimbleby H (2010) Inclusion and interaction: designing interaction for inclusive populations. Interact Comput 22(6):439–448CrossRefGoogle Scholar
  10. Pearl J (1982) Reverend bayes on inference engines: a distributed hierarchical approach. In: Proceedings of the American association of artificial intelligence national conference on AI, Pittsburgh, PA, USGoogle Scholar
  11. Salvucci DD, Lee FJ (2003) Simple cognitive modeling in a complex cognitive architecture. In: Proceedings of the ACM CHI 2003 human factors in computing systems conference, Ft Lauderdale, FL, USGoogle Scholar
  12. Thimbleby H (2010) Press on - Principles of interaction programming. MIT Press, CambridgeGoogle Scholar
  13. Wollner PKA, Hosking I, Langdon PM, Clarkson PJ (2013) Improvements in interface design through implicit modeling. In: Universal access in human-computer interaction. Design methods, tools, and interaction techniques for eInclusion. Lecture notes in computer science,vol 8009, pp 127–136Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • P. K. A. Wollner
    • 1
  • P. M. Langdon
    • 1
  • P. J. Clarkson
    • 1
  1. 1.Engineering Design Centre, Department of EngineeringUniversity of CambridgeCambridgeUK

Personalised recommendations