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  • 1.
    Çöltekin, Arzu
    et al.
    Department of Geography, University of Zurich.
    Francelet, Rebecca
    Department of Geography, University of Zurich.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Thoresen, John
    Laboratory of Behavioural Genetics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL).
    Fabrikant, Sara Irina
    Department of Geography, University of Zurich.
    The effects of visual realism, spatial abilities, and competition on performance in map-based route learning in men2018In: Cartography and Geographic Information Science, ISSN 1523-0406, E-ISSN 1545-0465, Vol. 45, no 4, p. 339-353Article in journal (Refereed)
    Abstract [en]

    We report on how visual realism might influence map-based route learning performance in a controlled laboratory experiment with 104 male participants in a competitive context. Using animations of a dot moving through routes of interest, we find that participants recall the routes more accurately with abstract road maps than with more realistic satellite maps. We also find that, irrespective of visual realism, participants with higher spatial abilities (high-spatial participants) are more accurate in memorizing map-based routes than participants with lower spatial abilities (low-spatial participants). On the other hand, added visual realism limits high-spatial participants in their route recall speed, while it seems not to influence the recall speed of low-spatial participants. Competition affects participants’ overall confidence positively, but does not affect their route recall performance neither in terms of accuracy nor speed. With this study, we provide further empirical evidence demonstrating that it is important to choose the appropriate map type considering task characteristics and spatial abilities. While satellite maps might be perceived as more fun to use, or visually more attractive than road maps, they also require more cognitive resources for many map-based tasks, which is true even for high-spatial users.

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