Effects of Display Size and Navigation Type on a Classification Task

Can Liu 1, 2, 3 Olivier Chapuis 1, 2 Michel Beaudouin-Lafon 1, 2 Éric Lecolinet 3 Wendy E. Mackay 1, 4
1 IN-SITU - Situated interaction
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
4 InSitu
LRI - Laboratoire de Recherche en Informatique
Abstract : The advent of ultra-high resolution wall-size displays and their use for complex tasks require a more systematic analysis and deeper understanding of their advantages and drawbacks compared with desktop monitors. While previous work has mostly addressed search, visualization and sense-making tasks, we have designed an abstract classification task that involves explicit data manipulation. Based on our observations of real uses of a wall display, this task represents a large category of applications. We report on a controlled experiment that uses this task to compare physical navigation in front of a wall-size display with virtual navigation using pan-and-zoom on the desktop. Our main finding is a robust interaction effect between display type and task difficulty: while the desktop can be faster than the wall for simple tasks, the wall gains a sizable advantage as the task becomes more difficult. A follow-up study shows that other desktop techniques (overview+detail, lens) do not perform better than pan-and-zoom and are therefore slower than the wall for difficult tasks.
Type de document :
Communication dans un congrès
Proceedings of the 32nd international conference on Human factors in computing systems, Apr 2014, Toronto, Canada. ACM, pp.4147-4156, 2014, CHI '14. 〈10.1145/2556288.2557020〉
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Contributeur : Olivier Chapuis <>
Soumis le : mardi 6 mai 2014 - 10:15:54
Dernière modification le : jeudi 5 avril 2018 - 12:30:23
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Can Liu, Olivier Chapuis, Michel Beaudouin-Lafon, Éric Lecolinet, Wendy E. Mackay. Effects of Display Size and Navigation Type on a Classification Task. Proceedings of the 32nd international conference on Human factors in computing systems, Apr 2014, Toronto, Canada. ACM, pp.4147-4156, 2014, CHI '14. 〈10.1145/2556288.2557020〉. 〈hal-00957269v2〉

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