Individual Differences in Route-Learning Strategy and Associated Working Memory Resources

Author:

Baldwin Carryl L.1,Reagan Ian2

Affiliation:

1. George Mason University, Fairfax, Virginia,

2. Old Dominion University, Norfolk, Virginia

Abstract

Objective: The current investigation examined individual differences in route-learning strategies and their relative demands on visuospatial versus verbal working memory (WM) resources in virtual environments. Background: Learning new routes is a resource-demanding activity that must often be carried out in conjunction with other concurrent tasks. Virtual environments (VEs) are increasingly being used for training and research, pointing to the importance of determining the strategies people use to learn routes in these environments. Methods: Participants classified as having good or poor sense of direction (SOD) attempted to learn novel routes while concurrently performing either a verbal (articulatory suppression) or a visuospatial (tapping) WM interference task. Results: Different navigational strategies were observed in each SOD group. Individuals with poor SOD relied more heavily on verbal rather than visuospatial WM resources, as evidenced by greater disruption to route-learning performance from the articulatory suppression task relative to the tapping task. Conversely, individuals with good SOD exhibited more route-learning disruption from the tapping task, suggesting a greater reliance on visuospatial WM resources. Conclusion: Individuals differ from one another in the strategies they use and the WM resources they tap—verbal or visuospatial—to learn routes in VEs. Self-report measures can be used as indices of such individual differences in navigational strategy use in VE tasks. Application: Assessing SOD and associated WM resources have implications for targeted training for navigation in VEs and for the design of in-vehicle navigation systems.

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

Reference53 articles.

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4. Working Memory

5. Baldwin, C.L. ( 2006). User-centered design of in-vehicle route guidance systems . In D. de Waard, K. Brookhuis, & A. Toffetti (Eds.), Developments in human factors in transportation, design, and evaluation (pp. 43-49). Maastricht , Netherlands: Shaker.

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