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Usability Metrics of Time and Stress - Biological Enhanced Performance Test of a University Wide Learning Management System

  • Christian Stickel
  • Alexei Scerbakov
  • Thomas Kaufmann
  • Martin Ebner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5298)

Abstract

This paper describes the modification and outcome of a performance test applied to a university wide learning management system under realistic conditions to identify usability problems and to compare measures such as success rate, task time and user satisfaction with requirements. Two user groups with 20 test users each took part in this study. During the whole test psycho-physiological parameters of the test persons were monitored and recorded, in order to find event related stress symptoms. Modifications of the original test allowed a faster analysis of relevant quantitative metrics and the collection of qualitative information.

Keywords

Usability Test Performance Measurement Self-Assessment EEG 

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References

  1. 1.
    Brooke, J.: SUS: a “quick and dirty” usability scale. In: Jordan, P.W., Thomas, B., Weerdmeester, B.A., McClelland, A.L. (eds.) Usability Evaluation in Industry. Taylor and Francis, London (1996)Google Scholar
  2. 2.
    de Boer, E.: On the residue and auditory pitch perception. In: Keidel, W.D. (ed.) Handbook of Sensors Physiology, pp. 479–583. Springer, Berlin (1976)Google Scholar
  3. 3.
    Ebner, M., Walder, U.: e-Learning in Civil Engineering – Six Years of Experience at Graz University of Technology. In: Rebolj, D. (ed.) Bringing ITC Knowledge to work, Proceeding of 24th W78 Conference Maribor 2007 & 14th EG-ICE Workshop & 5th ITC@EDU Workshop, pp. 749–754 (2007)Google Scholar
  4. 4.
    Evans, E.F.: Place and time coding of frequency in the peripheral auditory system:some physiological pros and cons. Audiology 17, 369–420 (1978)CrossRefGoogle Scholar
  5. 5.
    ISO The international Organization for Standardization : Ergonomic requirements for office work with visual display terminals (VDTs). Part 11: Guidance on usability (ISO 9241–11) (1998) Google Scholar
  6. 6.
    Holzinger, A., Ebner, M.: Interaction and Usability of Simulations & Animations: A case study of the Flash Technology. In: Proceedings of: Interact 2003, Zurich, pp. 777–780 (2003)Google Scholar
  7. 7.
    Holzinger, A.: Usability Engineering for Software Developers. Communications of the ACM 48(1), 71–74 (2005)CrossRefGoogle Scholar
  8. 8.
    Holzinger, A., Kickmeier-Rust, M., Albert, D.: Dynamic Media in Computer Science Education; Content Complexity and Learning Performance: Is Less More? Educational Technology & Society 11(1), 279–290 (2008)Google Scholar
  9. 9.
    Holzinger, A., Nischelwitzer, A., Meisenberger, M.: Mobile Phones as a Challenge for m-Learning: Examples for Mobile Interactive Learning Objects (MILOs). In: Proceedings of: Third IEEE International Conference on Pervasive Computing and Communication (Per-Com 2005), Kauai Island, HI, pp. 307–311 (2005)Google Scholar
  10. 10.
    Macleod, M.: Draft of chapter. In: Jordan, P. (ed.) Usability Evaluation in Industry. Taylor and Francis. Crown publishing, London (1994)Google Scholar
  11. 11.
    Moore, B.C.J.: Introduction to the Psychology of Hearing, 3rd edn. Academic Press, London (1989)Google Scholar
  12. 12.
    Müller-Putz, G.R., Scherer, R., Brauneis, C., Pfurtscheller, G.: Steady-state visual evoked potential (SSVEP)- based communication: impact of harmonic frequency compo-nents. Journal of Neural Engineering 2(4), 123–130 (2005)CrossRefGoogle Scholar
  13. 13.
    Picard, R.W.: Affective Computing. MIT Press, Cambridge (1997)CrossRefGoogle Scholar
  14. 14.
    Picard, R.W., Healey, J.: Affective Wearables. MIT Press, Cambridge (1997)CrossRefGoogle Scholar
  15. 15.
    Picard, R.W.: Perceptual user interfaces: affective perception. Communications of the ACM 43(3), 50–51 (2000)CrossRefGoogle Scholar
  16. 16.
    Rengger, R., Macleod, M., Bowden, R., Drynan, A., Blayney, M.: MUSiC Performance Measurement Handbook, V2. NPL, DITC, Teddington, UK (1993)Google Scholar
  17. 17.
    Riseberg, J., Klein, J., Fernandez, R., Picard, R.W.: Frustrating the user on purpose: using biosignals in a pilot study to detect the user’s emotional state. In: Conference on Human Factors in Computing Systems, Los Angeles, CA, pp. 227–228 (1998)Google Scholar
  18. 18.
    Murgg, E., Nischelwitzer, A.: Physiological Usability Testing: A Biological Approach to Detect and Measure Usability Problems. In: Multimedia Applications in Education Conference (MApEC) Proceedings 2004, pp. 122–127 (2004)Google Scholar
  19. 19.
    Stickel, C., Fink, J., Holzinger, A.: Enhancing Universal Access – EEG based Learnability Assessment. In: Stephanidis, C. (ed.) HCI 2007. LNCS, vol. 4556, pp. 813–822. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Christian Stickel
    • 1
  • Alexei Scerbakov
    • 1
  • Thomas Kaufmann
    • 1
  • Martin Ebner
    • 1
  1. 1.Zentraler Informatik Dienst / Vernetztes LernenGraz University of TechnologyGraz

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