Competing strategies in categorization: Expediency and resistance to knowledge restructuring.

Abstract

The authors investigated people's ability to restructure their knowledge when additional information about a categorization task is revealed. In 2 experiments, people first learned to rely on a fairly accurate (but imperfect) predictor. At various points in training, a complex relationship between 2 other predictors was revealed in a schematic diagram that could support perfect performance. In Experiment 1, people adopted the complex strategy when it was revealed at the outset but were unable to restructure their knowledge after the expedient predictor had been learned. In Experiment 2, expedient knowledge persisted even with an adaptive display. The persistence of expedient knowledge is explained by associative blocking of potential alternative cues. A 3rd experiment analyzed the strategies people use with and without the diagram. The study confirmed that the diagram, when presented at the outset, significantly alters people's approach to the task.Knowledge restructuring is often observed when people develop new skills, both in the real world and in the laboratory; paradoxically, expertise at these skills in some cases also seems to prevent restructuring of knowledge. Little is known about the processes involved in knowledge restructuring, and our investigation formed a first step toward describing those processes in order to better understand when restructuring occurs and when it is resisted.Specifically, we examined people's ability to adapt and restructure their knowledge when previously concealed information about a categorization task was revealed halfway through training. The task could be performed either by relying on an expedient single predictor that permitted fairly accurate (but imperfect) performance or by learning one of several complex (but potentially perfect) strategies involving two predictors. It was known from previous research that people can use a complex strategy for this task if the relationship between predictors is revealed in a schematic diagram before training (Lewandowsky, Dunn, Kirsner, & Randell, 1997). Here, we asked two questions: First, can people use the diagram to restructure their knowledge after having learned to rely on the expedient predictor, and what are the processes underlying that restructuring? Identification of those processes requires exploration of the second question, namely what exact strategy or rule people used with and without the diagram. We report three experiments in which the diagram was presented at various points in training.Stephan Lewandowsky, Mike Kalish, and Thomas L. Griffiths, Department of Psychology, University of Western Australia, Nedlands, Australia.Preparation of this article was facilitated by Large Research Grants A79600016 and A79941108 from the Australian Research Council. We thank Janet Phang and Lih Yi Soong for assistance during data collection and analysis, and Mike Mundy and Christina Chandler for help during preparation of this article.Correspondence concerning this article should be addressed to Stephan Lewandowsky, Department of...

Ad hoc category restructuring

“…Turning first to points of agreement, our results confirm the necessity of providing a hint about an alternative strategy, since no restructuring was observed when the reveal manipulation was withheld. This accords well with the findings by Kalish et al (2005) and Lewandowsky et al (2000), who similarly found that even after extended learning people did not spontaneously abandon one strategy in favor of another. Moreover, in Lewandowsky et al's study, when the alternative strategy was revealed after training, participants resisted knowledge restructuring and continued to use the originally learned strategy.…”

“…For this associative-learning account, all items should continue to be categorized into the appropriate training category if they are sufficiently learned. Although this basic idea is compatible with the results of Lewandowsky et al (2000) and Kalish et al (2005), a simple associative-learning view is constrained to expect identical outcomes for all item types, irrespective of whether or not experimental and preexperimental knowledge are in conflict.…”

“…This potential change in strategy, with no change in the nature of the task or the stimuli, is known as knowledge restructuring and has previously been examined in categorization using artificial stimuli (see, e.g., Kalish, Lewandowsky, & Davies, 2005;Lewandowsky, Kalish, & Griffiths, 2000). In the studies by Kalish et al (2005) and Lewandowsky et al (2000), restructuring from a simple (but imperfect) to a complex (but potentially perfect) categorization strategy occurred only if two conditions were met: First, the complex alternative strategy had to be explicitly pointed out to participants, and second, participants using the simple strategy had to be committing a considerable number of errors. When one or the other condition was not met, people resisted knowledge restructuring and continued to use the simple but imperfect strategy.…”

“…We adapted the knowledge restructuring methodology (Kalish et al, 2005;Lewandowsky et al, 2000) to examine the interplay of experimental and preexperimental knowledge in ad hoc categorization. We compared performance across three conditions: a condition in which the ad hoc category labels were available throughout the experiment, a control condition in which the ad hoc labels were never shown, and a condition in which the ad hoc labels were revealed after training.…”

Rule-based extrapolation: A continuing challenge for exemplar models

“…Because average data obscure differences among participants, a k-means clustering analysis was used to explore individual differences in participants' response profiles (see Erickson, 1999;Lewandowsky, Kalish, & Griffiths, 2000;Webb & Lee, 2004;Yang & Lewandowsky, 2003). Profiles consisted of responses to all stimuli across all five phases of the experiment.…”