Advertisement

Impact of Display Clutter on User Experience

  • Svetlana Ognjanovic
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10918)

Abstract

In human-technology interaction display properties are an integral part of a successful achievement of user goals. To assess display properties different approaches have been taken. Besides design and visualization research, displays also play a central role in Human Factors and Ergonomics, as well as in Usability and User Experience research. In Human Factors and Ergonomics research, Display Clutter is usually associated with the abundance of irrelevant information on a screen. Depending on the definition of clutter, poor display organization, or performance and attentional costs of the user are considered as clutter as well. In User Experience research display properties are divided into instrumental (e.g., usability, utility) and non-instrumental (e.g., visual aesthetics) qualities. The present paper puts the Display Clutter and the User Experience concept in relation. It becomes obvious that the two approaches pursue a similar goal, thus an optimal user-interaction with a technical system. From a theoretical point of view, however, there are clear differences. Also, from a methodological perspective, some measurement techniques, which include the computational quantification of the screen, are unique to Display Clutter. Nevertheless, user performance measures and user ratings are employed in both Display Clutter as well as in User Experience research. It is discussed how display clutter can influence users’ experience on several levels: Instrumental (i.e., pragmatic) and non-instrumental (i.e., hedonic), from an objective system property perspective as well as subjectively perceived user perspective.

Keywords

Display clutter Usability User experience Visual aesthetics 

References

  1. 1.
    Moacdieh, N., Sarter, N.: Display clutter: a review of definitions and measurement techniques. Hum. Factors 57(1), 61–100 (2014)CrossRefGoogle Scholar
  2. 2.
    Tullis, T.S.: The formatting of alphanumeric displays: a review and analysis. Hum. Factors 25, 657–682 (1983)CrossRefGoogle Scholar
  3. 3.
    Ververs, P.M., Wickens, C.D.: Head-up displays: effect of clutter, display intensity, and display location on pilot performance. Int. J. Aviat. Psychol. 8, 377–403 (1998)CrossRefGoogle Scholar
  4. 4.
    Mack, M.L., Oliva, A.: Computational estimation of visual complexity. In: Paper presented at the 12th Annual Object, Perception, Attention, and Memory Conference, Minneapolis, MN (2004)Google Scholar
  5. 5.
    Wolfe, J.M.: Guided search 2.0: a revised model of visual search. Psychon. Bull. Rev. 1, 202–238 (1994)CrossRefGoogle Scholar
  6. 6.
    Palmer, J.: Set-size effects in visual search: the effect of attention is independent of the stimulus for simple tasks. Vis. Res. 34, 1703–1721 (1994)CrossRefGoogle Scholar
  7. 7.
    Wickens, C.D., Hollands, J.G., Banbury, S., Parasuraman, R.: Engineering Psychology and Human Performance, 4th edn. Pearson Education, Upper Saddle River (2013)Google Scholar
  8. 8.
    Grahame, M., Laberge, J., Scialfa, C.T.: Age differences in search of web pages: the effects of link size, link number, and clutter. Hum. Factors 46, 385–398 (2004)CrossRefGoogle Scholar
  9. 9.
    Rosenholtz, R., Li, Y., Nakano, L.: Measuring visual clutter. J. Vis. 7(2), 1–22 (2007)CrossRefGoogle Scholar
  10. 10.
    Shneiderman, B., Plaisant, C., Cohen, M., Jacobs, S.: Designing the User Interface: Strategies for Effective Human-Computer Interaction, 5th edn. Prentice Hall, Upper Saddle River (2009)Google Scholar
  11. 11.
    Tullis, T.S.: Screen design. In: Helander, M. (ed.) Handbook of Human-Computer Interaction, pp. 377–411. North-Holland, Amsterdam (1988)CrossRefGoogle Scholar
  12. 12.
    Beck, M.R., Lohrenz, M.C., Trafton, J.G.: Measuring search efficiency in complex visual search tasks: global and local clutter. J. Exp. Psychol. Appl. 16, 238–250 (2010)CrossRefGoogle Scholar
  13. 13.
    Rosenholtz, R.: A simple saliency model predicts a number of motion popout phenomena. Vis. Res. 39, 3157–3163 (1999)CrossRefGoogle Scholar
  14. 14.
    Moore, R.K.: Masked target transform volume clutter metric for human observer visual search modeling (Doctoral dissertation). Available from ProQuest Dissertations and Theses database (UMI No. 3400193) (2009)Google Scholar
  15. 15.
    Xu, D., Shi, Z., Luo, H.: A structural difference based image clutter metric with brain cognitive model constraints. Infrared Phys. Technol. 57, 28–35 (2012)CrossRefGoogle Scholar
  16. 16.
    Chu, X., Yang, C., Li, Q.: Contrast-sensitivity-function-based clutter metric. Opt. Eng. 51(6), 067003 (2012)CrossRefGoogle Scholar
  17. 17.
    Alexander, A.L., Stelzer, E.M., Kim, S.-H., Kaber, D.B.: Bottom-up and top-down contributors to pilot perceptions of display clutter in advanced flight deck technologies. In: Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting, pp. 1180–1184. Human Factors and Ergonomics Society, Santa Monica (2008)CrossRefGoogle Scholar
  18. 18.
    Rosenholtz, R., Li, Y., Mansfield, J., Jin, Z.: Feature congestion: a measure of display clutter. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 761–770. ACM Press, New York (2005)Google Scholar
  19. 19.
    Neider, M.B., Zelinsky, G.J.: Cutting through the clutter: searching for targets in evolving complex scenes. J. Vis. 11(14), 7 (2011)CrossRefGoogle Scholar
  20. 20.
    Beck, M.R., Trenchard, M., van Lamsweerde, A., Goldstein, R.R., Lohrenz, M.: Searching in clutter: visual attention strategies of expert pilots. In: Proceedings of the Human Factors and Ergonomics Society 56th Annual Meeting, pp. 1411–1415. Human Factors and Ergonomics Society, Santa Monica (2012)CrossRefGoogle Scholar
  21. 21.
    Goldberg, J.H., Kotval, X.P.: Computer interface evaluation using eye movements: methods and constructs. Int. J. Ind. Ergon. 24, 631–645 (1999)CrossRefGoogle Scholar
  22. 22.
    Kim, S.-H., Prinzel, L.J., Kaber, D.B., Alexander, A.L., Stelzer, E.M., Kaufmann, K., Veil, T.: Multidimensional measure of display clutter and pilot performance for advanced head-up display. Aviat. Space Environ. Med. 82, 1013–1022 (2011)CrossRefGoogle Scholar
  23. 23.
    Kaber, D., Kim, S.-H., Kaufmann, K., Alexander, A., Steltzer, E., Hsiang, S.: Modeling the effects of HUD visual properties, pilot experience and flight scenario on a multi-dimensional measure of clutter. Langley Research Center, Hampton (2008)Google Scholar
  24. 24.
    Naylor, J.: The influence of dynamics, flight domain and individual flight training & experience on pilot perception of clutter in aviation displays (Master’s thesis) (2010). http://repository.lib.ncsu.edu/ir/handle/1840.16/6103
  25. 25.
    Alexander, A.L., Kaber, D.B., Kim, S.-H., Stelzer, E.M., Kaufmann, K., Prinzel III, L.J.: Measurement and modeling of display clutter in advanced flight deck technologies. Int. J. Aviat. Psychol. 22, 299–318 (2012)CrossRefGoogle Scholar
  26. 26.
    Kaufmann, K., Kaber, D.B.: The influence of individual differences in perceptual performance on pilot perceptions of head-up display clutter. In: Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting, pp. 70–74. Human Factors and Ergonomics Society, Santa Monica (2010)CrossRefGoogle Scholar
  27. 27.
    Kaber, D.B., Alexander, A., Kaufmann, K., Kim, S.H., Naylor, J.T., Entin, E.: Testing and validation of a psychophysically defined metric of display clutter (Final Report: NASA Langley Research Center Grant. NNL06AA21A). NASA Langley Research Center, Hampton, VA (2009)Google Scholar
  28. 28.
    Tufte, E.: The Visual Display of Quantitative Information, 2nd edn. Graphics Press, Cheshire (1983)Google Scholar
  29. 29.
    Nielsen, J.: Heuristic evaluation. In: Nielsen, J., Mack, R.L. (eds.) Usability Inspection Methods. Wiley, New York (1994)CrossRefGoogle Scholar
  30. 30.
    Rich, B.R.: Clarence Leonard (Kelly) Johnson: 1910–1990: A Biographical Memoir, p. 13. National Academies Press, Washington (1995)Google Scholar
  31. 31.
    Hassenzahl, M., Kekez, R., Burmester, M.: The importance of software’s pragmatic quality depends of usage modes. In: Luczak, H., Çakir, A.E., Çakir, G. (eds.) Proceedings of the 6th International Conference on Work With Display Units (WWDU 2002), pp. 275–276. Ergonomic Institut für Arbeits- und Sozialforschung, Berlin (2002)Google Scholar
  32. 32.
    Mahlke, S.: User Experience of Interaction with Technical Systems: Theories, Methods, Empirical Results, and Their Application to the Design of Interactive Systems. VDM Verlag, Saarbrücken (2008)Google Scholar
  33. 33.
    Shackel, B.: Usability - context, framework, design and evaluation. In: Shackel, B., Richardson, S. (eds.) Human Factors for Informatics Usability, pp. 21–38. Cambridge University Press, Cambridge (1991)zbMATHGoogle Scholar
  34. 34.
    Nielsen, J.: Usability Engineering. Academic Press, San Diego (1993)zbMATHGoogle Scholar
  35. 35.
    ISO 9241-11: Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability. International Standardization Organization (ISO), Geneva (1998, 2015)Google Scholar
  36. 36.
    Lindgaard, G., Dudek, C.: What is this evasive beast we call user satisfaction? Interact. Comput. 15(3), 429–452 (2003)CrossRefGoogle Scholar
  37. 37.
    Mahlke, S., Lemke, I., Thüring, M.: The diversity of non-instrumental qualities in human-technology interaction. mmi interaktiv 13, 55–64 (2007)Google Scholar
  38. 38.
    Hassenzahl, M.: Aesthetics in interactive products: correlates and consequences of beauty. In: Schifferstein, H.N.J., Hekkert, P. (eds.) Product Experience. Elsevier, Amsterdam (2007)Google Scholar
  39. 39.
    Kirakowski, J.: The software usability measurement inventory: background and usage. In: Jordan, P.W., Thomas, B., Weerdmeester, B.A., McClelland, I.L. (eds.) Usability Evaluation in Industry, pp. 169–178. Taylor & Francis, London (1996)Google Scholar
  40. 40.
    Lavie, T., Tractinsky, N.: Assessing dimensions of perceived visual aesthetics of websites. Int. J. Hum Comput Stud. 60(3), 269–298 (2004)CrossRefGoogle Scholar
  41. 41.
    Lavie, T., Oron-Gilad, T., Meyer, J.: Aesthetics and usability of in-vehicle navigation displays. Int. J. Hum Comput Stud. 69(1), 80–99 (2011)CrossRefGoogle Scholar
  42. 42.
    Moshagen, M., Thielsch, M.T.: Facets of visual aesthetics. Int. J. Hum Comput Stud. 68(10), 689–709 (2010)CrossRefGoogle Scholar
  43. 43.
    Thüring, M., Mahlke, S.: Usability, aesthetics and emotions in human–technology interaction. Int. J. Psychol. 42(4), 253–264 (2007)CrossRefGoogle Scholar
  44. 44.
    ISO 9241-210: Ergonomics of Human-System Interaction – Part 210: Human-Centred Design Process for Interactive Systems. International Standardization Organization (ISO), Geneva (2010)Google Scholar
  45. 45.
    Hassenzahl, M.: The hedonic/pragmatic model of user experience. In: Law, E., Vermeeren, A., Hassenzahl, M., Blythe, M. (eds.) Towards a UX Manifesto – Proceedings of a Cost-Affiliated Workshop on HCI 2008, pp. 10–14 (2007)Google Scholar
  46. 46.
    Roto, V.: User experience from product creation perspective. In: Law, E., Vermeeren, A., Hassenzahl, M., Blythe, M. (eds.) Towards a UX Manifesto – Proceedings of a Cost-Affiliated Workshop on HCI 2008, pp. 31–34 (2007)Google Scholar
  47. 47.
    Minge, M., Wagner, I., Thüring, M.: Developing and validating and english version of the meCUE questionnaire for measuring user experience. In: Proceedings of the 60th Annual Meeting of the Human Factors and Ergonomics Society 2016, pp. 2056–2060. Sage Publications, New York (2016)CrossRefGoogle Scholar
  48. 48.
    Minge, M., Thüring, M.: Hedonic and pragmatic halo effects at early stages of user experience. Int. J. Hum Comput Stud. 109, 13–25 (2018)CrossRefGoogle Scholar
  49. 49.
    Bargas-Avila, J.A., Hornbæk, K.: Old wine in new bottles or novel challenges: a critical analysis of empirical studies of user experience. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2689–2698. ACM, May 2011Google Scholar
  50. 50.
    Burmester, M., Zeiner, K.M., Laib, M., Hermosa Perrino, C., Queßeleit, M.-L.: Experience design and positive design as an alternative to classical human factors approaches. In: Beckmann, C., Gross, T. (eds.) INTERACT 2015 Adjunct Proceedings, pp. 153–160. University of Bamberg Press, Bamberg (2015)Google Scholar
  51. 51.
    Harbich, S., Hassenzahl, M.: Beyond task completion in the workplace: execute, engage, evolve, expand. In: Peter, C., Beale, R. (eds.) Affect and Emotion in Human-Computer Interaction. LNCS, vol. 4868, pp. 154–162. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-85099-1_13CrossRefGoogle Scholar
  52. 52.
    Lu, Y., Roto, V.: Evoking meaningful experiences at work–a positive design framework for work tools. J. Eng. Des. 26(4–6), 99–120 (2015)CrossRefGoogle Scholar
  53. 53.
    Zeiner, K.M., Laib, M., Schippert, K., Burmester, M.: Identifying experience categories to design for positive experiences with technology at work. In: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 3013–3020. ACM, New York (2016)Google Scholar
  54. 54.
    Seckler, M., Opwis, K., Tuch, A.N.: Linking objective design factors with subjective aesthetics: an experimental study on how structure and color of websites affect the facets of users’ visual aesthetic perception. Comput. Hum. Behav. 49, 375–389 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Chair of Cognitive ScienceETH ZurichZurichSwitzerland

Personalised recommendations