Problem Solving with Information Access Costs in Mind
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Problem Solving with Information Access Costs in Mind. Samuel. M Waldron, John Patrick, Andrew Howes & Geoffrey. B Duggan School of Psychology, Cardiff University, Cardiff, CF10 3AT, UK. Abstract

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Problem Solving with Information Access Costs in Mind

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Problem solving with information access costs in mind

Problem Solving with Information Access Costs in Mind

Samuel. M Waldron, John Patrick, Andrew Howes & Geoffrey. B Duggan

School of Psychology, Cardiff University, Cardiff, CF10 3AT, UK

Abstract

Problem solving is often conducted within the context of an external display. However, the time, physical effort, and mental effort associated with accessing information from such displays may vary. The current experiment demonstrated that an increased cost associated with accessing goal state information from a problem solving modification of the Blocks World Task (Ballard, Hayhoe, & Pelz, 1995), induced a shift in search strategies from largely perceptual-motor to memory-intensive. Consequences for the use of initial and concurrent planning are discussed.

Blocks Problem Solving Task

The aim of the Blocks Problem Solving Task (BPST) is to rearrange the configuration of the 16 blocks in the Workspace Window to recreate the pattern dictated by the Target Window. Only one coloured block can be moved at a time into an adjacent empty (white) space. Blocks are moved by clicking on the block to-be-moved, and then pressing the corresponding arrow key on the keyboard.

Target Window

Workspace Window

Adaptive Planning

When solving a problem within the context of an external display, adaptation to costs within the environment can influence the extent to which we choose to plan. O’Hara & Payne (1998) stated that “problem solving search strategies are chosen so as to optimize performance within the constraints of a particular situation” (p.34).

Information Access Cost

Planning research often assumes that the information needed to solve a problem is either readily available in the world, or is held in memory. The converse, however, is often true of problem solving in many applied situations. A pilot who is faced with the unexpected task of re-routing, for example, may have to evaluate information from a number of different sources, each with a different access cost. Using the Blocks World Task, Gray, Simms, Fu,& Schoelles (in press) have demonstrated that as the IAC increases during routine copying behaviour, interactive behaviour shifts away from perceptual-motor strategies, and towards memory-intensive strategies. That is, the extent to which individuals rely upon the display as an external memory source reduces as the cost associated with accessing information from the display increases.

Method

Participants. Thirty-six Cardiff University undergraduate Psychology students participated in the study for course credit and were randomly assigned to one of three conditions.

Materials. The experiment was presented to participants via a Tobii 1750 eye-tracker monitor. All eye movements, mouse movements and key presses were recorded.

Design.The IAC was manipulated on three levels:

Low IAC: Target window permanently uncovered.

Medium IAC: Target window covered by a grey mask. Uncovered by placing the mouse cursor over the window.

High IAC: Additional 2.5 second delay upon opening target window.

Procedure. Each participant experienced two practice trials and twelve different BPST problems in one of 4 randomised orders.

Aim of Experiment

The current experiment aimed to assess the extent to which problem solving search strategies would be sensitive to changes in IAC, and would influence planning behaviour.

Results & Discussion

A 3-way ANOVA was conducted upon the data.

Table 1 indicates that as the IAC increased, so did trial duration,

F(2,33) = 9.69, p <.001. The number of moves required to solve

each problem was, however, unaffected by IAC, F(2,33) = 0.84, p >.05.

Table 1 also indicates that as the IAC increased participants chose

to access the target window less frequently, F(2,33) = 191.65, p <.001,

and spent longer viewing the target window per trial, F(2,33) = 7.39, p

<.01. This result further supports the claim that as the cost of accessing

information within an interface increases, a shift in behaviour is

witnessed, away from perceptual-motor strategies, towards memory-

intensive strategies (Gray et al., in press). Note. Values represent trial means.

Moreover, the number of moves made per target visit increased dramatically in conjunction with the IAC, F(2,33) = 63.09, p <.001, (see Figure 1). Participants in the high IAC condition often made as many as 9 moves per visit, compared to an average of just over 1 move per visit when the IAC was low. Coupled with the fact that the time between each move (inter-move latency) decreased as the IAC increased, F(2,33) 6.62, p <.01, (see Figure 2) we can assume that the majority of the moves made in the workspace window by participants in the high IAC condition were pre-planned. Conversely, the majority of the moves made in the workspace window by participants in the low IAC condition included an inspection of the target window.

Figure 1: Effect of IAC on moves per target visit Figure 2: Effect of IAC on inter-move latency

Davies (2003) distinguished between the use of initial and concurrent planning when solving well-structured problems such as the one used here. The current experiment suggests that individuals engaged in more initial planning in response to an increased cost associated with accessing goal state information from the interface, and more concurrent planning when goal state information was readily available.

Table 1

Effect of IAC on BPST performance

Implications

There is currently much attention within the applied literature devoted to increasing the accessibility of information within the interface of complex systems (e.g., Vicente, 2002). The current study demonstrates that even very small changes in the accessibility of information within the task environment can have large consequences for how the information is processed.

References

Ballard, D. H., Hayhoe, M. M., & Pelz, J. B. (1995). Memory representations in natural tasks. Journal of Cognitive Neuroscience, 7(1), 66-80.

Davies, S. P. (2003). Initial and concurrent planning in solutions to well-structures problems. The Quarterly Journal of Experimental Psychology, 56A(7), 1147-1164.

Gray, W. D., Sims, C. R., Fu, W.-T., & Schoelles, M. J. (in press). The soft constraints hypothesis. A rational analysis approach to resource allocation for interactive behaviour. Psychological Review.

O’Hara, K. P. & Payne, S. J. (1998). The effects of operator implementation cost on planfulness of problem solving and learning. Cognitive Psychology, 35, 34-70.


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