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Elizabeth Chrastil, William Warren; Learning a new city: Active and passive components of spatial learning. Journal of Vision 2010;10(7):1039. doi: 10.1167/10.7.1039.
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© ARVO (1962-2015); The Authors (2016-present)
When arriving in a new city, how do you learn its layout? It seems that actively walking around would lead to better spatial knowledge than passively riding in a taxi, yet the literature is decidedly mixed. However, ""active"" learning has several components that are often confounded. We test the contributions of four components to spatial learning: visual information, vestibular information, motor/proprioceptive information, and cognitive decisions. Participants learn the locations of 10 objects in an ambulatory virtual maze environment, and are then tested on their graph and survey knowledge of object locations. Six learning conditions are crossed with two test conditions, for a total of 12 groups of participants: (a) Free Walking: participants freely explore the environment for 10 minutes, providing all components of active exploration. (b) Guided Walking: participants are guided along the same paths, removing the decision-making component. (c) Free Wheelchair: participants steer through the maze in a wheelchair by pressing buttons to indicate left and right turns, minimizing motor/proprioceptive information. (d) Guided Wheelchair: participants are wheeled through the maze along paths that match the Free Walking condition, removing motor/proprioception and decision-making, (e) Free Video: participants steer through a desktop VR maze by pressing buttons, removing motor/proprioceptive and vestibular information. (f) Guided Video: participants watch a participant's-eye video of the Free Walking condition, providing passive learning. In the test phase, participants are wheeled to object A and instructed to walk to the remembered location of object B: (i) Survey knowledge task: the maze disappears and participants take a direct shortcut from A to B. (ii) Graph knowledge task: participants walk from A to B within the maze corridors, with detours. We expect that active decisions will be sufficient for graph knowledge, whereas active motor/proprioceptive and/or vestibular information will be necessary for metric knowledge, and both will surpass passive learning.
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