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Advances in Human-Computer Interaction
Volume 2013, Article ID 879563, 7 pages
Research Article

Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks

1Aix-Marseille Université, CNRS, ISM UMR 7287, 13288 Marseille Cedex 09, France
2Université Victor Segalen Bordeaux II, Laboratoire Handicap et Système Nerveux EA 4136, 33076 Bordeaux Cedex, France
3INRIA, PHOENIX Team, Bordeaux Sud-Ouest, 400 Avenue de la Vieille Tour, 33400 Talence, France

Received 14 May 2013; Revised 13 August 2013; Accepted 27 August 2013

Academic Editor: Ian Oakley

Copyright © 2013 Grégory Wallet et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The purpose of this study was to examine the effect of navigation mode (passive versus active) on the virtual/real transfer of spatial learning, according to viewpoint displacement (ground: 1 m 75 versus aerial: 4 m) and as a function of the recall tasks used. We hypothesize that active navigation during learning can enhance performances when route strategy is favored by egocentric match between learning (ground-level viewpoint) and recall (egocentric frame-based tasks). Sixty-four subjects (32 men and 32 women) participated in the experiment. Spatial learning consisted of route learning in a virtual district (four conditions: passive/ground, passive/aerial, active/ground, or active/aerial), evaluated by three tasks: wayfinding, sketch-mapping, and picture-sorting. In the wayfinding task, subjects who were assigned the ground-level viewpoint in the virtual environment (VE) performed better than those with the aerial-level viewpoint, especially in combination with active navigation. In the sketch-mapping task, aerial-level learning in the VE resulted in better performance than the ground-level condition, while active navigation was only beneficial in the ground-level condition. The best performance in the picture-sorting task was obtained with the ground-level viewpoint, especially with active navigation. This study confirmed the expected results that the benefit of active navigation was linked with egocentric frame-based situations.