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

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 d...

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Main Authors: Grégory Wallet, Hélène Sauzéon, Florian Larrue, Bernard N'Kaoua
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Advances in Human-Computer Interaction
Online Access:http://dx.doi.org/10.1155/2013/879563
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author Grégory Wallet
Hélène Sauzéon
Florian Larrue
Bernard N'Kaoua
author_facet Grégory Wallet
Hélène Sauzéon
Florian Larrue
Bernard N'Kaoua
author_sort Grégory Wallet
collection DOAJ
description 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.
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institution Kabale University
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publishDate 2013-01-01
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spelling doaj-art-93bd7ced612c4e9aae69adee6e7b938c2025-02-03T01:12:35ZengWileyAdvances in Human-Computer Interaction1687-58931687-59072013-01-01201310.1155/2013/879563879563Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall TasksGrégory Wallet0Hélène Sauzéon1Florian Larrue2Bernard N'Kaoua3Aix-Marseille Université, CNRS, ISM UMR 7287, 13288 Marseille Cedex 09, FranceUniversité Victor Segalen Bordeaux II, Laboratoire Handicap et Système Nerveux EA 4136, 33076 Bordeaux Cedex, FranceUniversité Victor Segalen Bordeaux II, Laboratoire Handicap et Système Nerveux EA 4136, 33076 Bordeaux Cedex, FranceUniversité Victor Segalen Bordeaux II, Laboratoire Handicap et Système Nerveux EA 4136, 33076 Bordeaux Cedex, FranceThe 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.http://dx.doi.org/10.1155/2013/879563
spellingShingle Grégory Wallet
Hélène Sauzéon
Florian Larrue
Bernard N'Kaoua
Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks
Advances in Human-Computer Interaction
title Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks
title_full Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks
title_fullStr Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks
title_full_unstemmed Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks
title_short Virtual/Real Transfer in a Large-Scale Environment: Impact of Active Navigation as a Function of the Viewpoint Displacement Effect and Recall Tasks
title_sort virtual real transfer in a large scale environment impact of active navigation as a function of the viewpoint displacement effect and recall tasks
url http://dx.doi.org/10.1155/2013/879563
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