Prospective project: The effect of viewpoint selection and workload on the
evaluation of configurational knowledge in virtual environments.

Introduction

It has been demonstrated that virtual environments (VEs) can be used to
train spatial knowledge of real-world spaces (Koh et al, 1999).  However
evaluating configurational knowledge, i.e. the knowledge of the
three-dimensional layout of the space and the spatial relationships of
landmarks to one another, as opposed to other types of knowledge such
as route knowledge, has been difficult.  Traditional methods, such as
map sketching (Lynch, 1960; Appleyard, 1970) raise difficulties in
translation of the task output into a quantifiable score, and do not
seem to scale easily to the third dimension.  Pick-and-place map
reconstruction tasks have been used with success in the real world,
by moving magnets, paper cutouts or similar physical representations
of landmarks on a board, and scoring based on various position error
metrics (Sherman, Croxton and Giovanatto, 1979; Baird and Wagner, 1983;
Wickens and Prevett, 1995; Waller, 1999).

Again, it is mechanically difficult to scale these real-world tasks to the
third dimension, but I suggest that a three-dimensional pick-and-place
task for evaluating configurational knowledge could be implemented using
non-immersive virtual environment technology.  By representing the shell
of the space as a three-dimensional model, and allowing the subject to
place smaller models representing landmarks with a three degree-of-freedom
hand tracker, the task could be extended to the third dimension without
the problems introduced by real-world constraints such as gravity.

However, such a pick-and-place task is assisted through visual cues that
are poorly represented in VEs in general, and especially so in
non-immersive VEs.  These include stereopsis and motion parallax (Durlach
and Mavor, 1995).  In a non-immersive setting, this can be alleviated
somewhat by giving the subject the ability to perform continuous viewpoint
selection, allowing them to simulate motion parallax and provide
themselves with different perspective projections.  This can be thought of
as supervisory control over the affective output of the system.  On the
other hand, it could also be argued that because viewpoint control
necessitates some extra degree of decision making, it adds to the mental
workload of the subject and may detract from the task itself.

I propose an investigation of the effect of viewpoint selection on a
simple three-dimensional pick-and-place task designed to evaluate
configurational knowledge of an example room layout.  Conclusions will
be drawn based on the ability of subjects to accurately recreate a
memorised spatial arrangement, under several visual interfaces.  In
addition, the general tradeoff between interface fidelity and mental
workload will be discussed.

References

Appleyard, D. (1970)  Styles and Methods of Structuring a City.
Environment and Behaviour, 2, pp.110-118.

Baird, J.C. and Wagner, M. (1983)  Modeling the Creation of Cognitive
Maps.  In Pick, H. and Acredolo, L. (Eds.), Spatial Orientation.  Plenum.

Durlach, N.I. and Mavor, A.S. (Eds.) (1995)  Virtual Reality: Scientific
and Technical Challenges.  National Academy Press.

Koh, G., von Wiegand, T.E., Garnett, R.L., and Durlach, N.I. (1999)  Use
of Virtual Environments for Acquiring Configurational Knowledge About
Specific Real-World Spaces.  Presence: Teleoperators and Virtual
Environments, 8(6), pp.632-656.

Lynch, K. (1960) The Image of a City.  MIT Press.

Sherman, R.C., Croxton, J., and Giovanatto, J. (1979)  Investigating
Cognitive Representations of Spatial Relationships.  Environment and
Behaviour, 11(2), pp.209-226.

Waller, D.A. (1999)  An Assessment of Individual Differences in Spatial
Knowledge of Real and Virtual Environments.  Unpublished doctoral
dissertation, University of Washington, Seattle.

Wickens, C.D. and Prevett, T.T. (1995)  Exploring the Dimensions of
Egocentricity in Aircraft Navigation Displays.  Journal of Experimental
Psychology Applied, 1(2), pp.110-135.