Requirements for Applying Simulation-Based Automated Usability Evaluation to Model-Based Adaptive User Interfaces for Smart Environments

  • Michael Quade
  • Andreas Rieger
  • Sahin Albayrak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8028)


Users in smart environments benefit from context-aware applications that are able to adapt their user interfaces (UI) to specific situations. In the same way as the development of adaptive applications poses high demands on the designers, the evaluation of their usability also becomes more complex and time consuming because the context of use and different adaptation variants need to be considered. While automated usability evaluations cannot fully replace user tests in this domain, they can be applied to multiple adaptation variants at an early stage of development and thus reduce time and complexity. This paper presents general requirements for applying automated model-based usability evaluations that apply simulated user interaction as an approach to evaluate UIs of adaptive applications based on the underlying development models.


automated usability evaluation adaptive user interfaces modelbased UI development smart environments 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abrahão, S., Iborra, E., Vanderdonckt, J.: Usability evaluation of user interfaces generated with a model-driven architecture tool. In: Maturing Usability. Human-Computer Interaction Series, pp. 3–32. Springer, London (2008), CrossRefGoogle Scholar
  2. 2.
    Blackmon, M.H., Kitajima, M., Polson, P.G.: Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs. In: CHI 2005: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 31–40. ACM, New York (2005)Google Scholar
  3. 3.
    Blumendorf, M., Lehmann, G., Roscher, D., Albayrak, S.: Ubiquitous User Interfaces: Multimodal Adaptive Interaction for Smart Environments. In: Multimodality in Mobile Computing and Mobile Devices: Methods for Adaptable Usability, pp. 24–52. IGI-Global (2009)CrossRefGoogle Scholar
  4. 4.
    Feuerstack, S., Blumendorf, M., Kern, M., Kruppa, M., Quade, M., Runge, M., Albayrak, S.: Automated usability evaluation during model-based interactive system development. In: Forbrig, P., Paternò, F. (eds.) HCSE/TAMODIA 2008. LNCS, vol. 5247, pp. 134–141. Springer, Heidelberg (2008)Google Scholar
  5. 5.
    Hassenzahl, M., Schöbel, M., Trautmann, T.: How motivational orientation influences the evaluation and choice of hedonic and pragmatic interactive products: The role of regulatory focus. Interacting with Computers 20(4-5), 473–479 (2008), CrossRefGoogle Scholar
  6. 6.
    Ivory, M.Y., Hearst, M.A.: The state of the art in automating usability evaluation of user interfaces. ACM Comput. Surv. 33(4), 470–516 (2001)CrossRefGoogle Scholar
  7. 7.
    Jameson, A.: Adaptive interfaces and agents. In: Sears, A., Jacko, J.A. (eds.) The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications, 2nd edn., pp. 433–458. CRC Press, Boca Raton (2008)Google Scholar
  8. 8.
    Keates, S., Clarkson, J., Robinson, P.: Investigating the applicability of user models for motion-impaired users. In: Proceedings of the Fourth International ACM Conference on Assistive Technologies, Assets 2000, pp. 129–136. ACM, New York (2000)Google Scholar
  9. 9.
    Kobsa, A.: Generic user modeling systems. User Modeling and User-Adapted Interaction 11(1-2), 49–63 (2001)CrossRefzbMATHGoogle Scholar
  10. 10.
    Norman, D.A.: Some Observations on Mental Models. In: Mental Models, pp. 7–14. Erlbaum, Hillsdale (1983)Google Scholar
  11. 11.
    Quade, M., Lehmann, G., Engelbrecht, K.P., Roscher, D., Albayrak, S.: Automated usability evaluation of model-based adaptive user interfaces for users with special and specific needs by simulating user interaction. In: Martín, E., Haya, P.A., Carro, R.M. (eds.) User Modeling and Adaptation for Daily Routines. Human-Computer Interaction Series, vol. 9, pp. 219–247. Springer, London (2013)CrossRefGoogle Scholar
  12. 12.
    Ruß, A., Quade, M., Kruppa, M., Runge, M.: Rule-based approach for simulating age-related usability problems. In: Wichert, R., Eberhardt, B. (eds.) Ambient Assisted Living. Advanced Technologies and Societal Change, vol. 2, pp. 149–166. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Schilit, B., Adams, N., Want, R.: Context-aware computing applications. In: IEEE Workshop on Mobile Computing Systems and Applications, Santa Cruz, CA, US (1994)Google Scholar
  14. 14.
    Sottet, J.S., Calvary, G., Coutaz, J., Favre, J.M.: A Model-Driven Engineering Approach for the Usability of Plastic User Interfaces. In: Gulliksen, J., Harning, M.B., van der Veer, G.C., Wesson, J. (eds.) EIS 2007. LNCS, vol. 4940, pp. 140–157. Springer, Heidelberg (2008), Google Scholar
  15. 15.
    Teo, L., John, B.E.: The evolution of a goal-directed exploration model: Effects of information scent and goback utility on successful exploration. Topics in Cognitive Science 3(1), 154–165 (2011)CrossRefGoogle Scholar
  16. 16.
    Trewin, S., Pain, H.: Keyboard and mouse errors due to motor disabilities. Int. J. Hum.-Comput. Stud. 50(2), 109–144 (1999), CrossRefGoogle Scholar
  17. 17.
    Vanderdonckt, J., Guerrero-Garcia, J., González-Calleros, J.M.: A model-based approach for developing vectorial user interfaces. In: Proceedings of the LA-WEB 2009 (2009)Google Scholar
  18. 18.
    Goldsby, H.J., Cheng, B.H.C., Zhang, J.: AMOEBA-RT: Run-time verification of adaptive software. In: Giese, H. (ed.) MODELS 2008. LNCS, vol. 5002, pp. 212–224. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Michael Quade
    • 1
  • Andreas Rieger
    • 1
  • Sahin Albayrak
    • 1
  1. 1.DAI-LaborTechnische Universität BerlinBerlinGermany

Personalised recommendations