Errors, efficiency, and the interplay between attention and category learning

Blair, Mark R.; Watson, Marcus R.; Meier, Kimberly

doi:10.1016/j.cognition.2009.04.008

Cited by 47 publications

(68 citation statements)

References 38 publications

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“…For example, Blair et al (2009a) found that learners continued to optimize attention even after a criterion of 24 correct trials was reached and feedback stopped altogether. Of course, attentional shifts in the absence of feedback pose problems for all category learning models that tie attentional learning to error-driven mechanisms (e.g., Kruschke, 1992).…”

Section: Discussionmentioning

confidence: 99%

“…In cognitive research, eyetracking has been proven to be an effective tool to study on-line attention (e.g., Ferreira & Clifton, 1986;Haider & Frensch, 1999;Just & Carpenter, 1984;Lee & Anderson, 2001;Rayner, 1998). In recent years, it has been successfully applied to studying selective attention in category learning in the absence of knowledge (Blair et al, 2009a;Blair, Watson, Walshe, & Maj, 2009b;Rehder & Hoffman, 2005a, 2005bRehder, Colner, & Hoffman, 2009;Watson & Blair, 2008). We now use eyetracking to study how attention is affected by prior knowledge.…”

Section: How Knowledge Might Affect Attentionmentioning

confidence: 99%

“…Alternatively, shifts in attention may also arise in the absence of error. That prior knowledge affects how subjects spontaneously sort exemplars into categories (and possibly which features are attended) in category construction tasks in which corrective feedback is absent (e.g., Kaplan & Murphy, 1999;Medin, Wattenmaker, & Hampson, 1987;Spalding & Murphy, 1996) suggests that attention may shift even on those trials during a supervised learning task in which error is absent (Blair, Watson, & Meier, 2009a).…”

Section: How Knowledge Might Affect Attentionmentioning

confidence: 99%

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How prior knowledge affects selective attention during category learning: An eyetracking study

Kim

Rehder

2010

Mem Cogn

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Research has shown that category learning is affected by (a) attention, which selects which aspects of stimuli are available for further processing, and (b) the existing semantic knowledge that learners bring to the task. However, little is known about how knowledge affects what is attended. Using eyetracking, we found that (a) knowledge indeed changes what features are attended, with knowledge-relevant features being fixated more often than irrelevant ones, (b) this effect was not due to an initial attentional bias toward relevant dimensions but rather emerged gradually as a result of observing category members, and (c) this effect grew even after a learning criterion was reached, that is, despite the absence of negative feedback. We argue that models of knowledgebased learning will remain incomplete until they specify mechanisms that dynamically select prior knowledge in response to observed category members and which then directs attention to knowledge-relevant dimensions and away from irrelevant ones.

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Section: Discussionmentioning

confidence: 99%

Section: How Knowledge Might Affect Attentionmentioning

confidence: 99%

Section: How Knowledge Might Affect Attentionmentioning

confidence: 99%

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How prior knowledge affects selective attention during category learning: An eyetracking study

Kim

Rehder

2010

Mem Cogn

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“…Shepherd, Findlay, and Hockey (1986) demonstrated that although attending without making corresponding eye movements is possible, it is not possible to make an eye movement without shifting attention. More generally, the close link between attention and eye movements has been shown across a variety of cognitive tasks (see Liversedge &Findlay, 2000, andRayner, 1998, for reviews; also see Blair, Watson, & Meier, 2009;Blair, Watson, Walshe, & Maj, 2009). Mechanisms of attention are neurally and behaviorally coupled with eye movements.…”

Section: Using Eye Fixations To Measure Attentionmentioning

confidence: 99%

The costs of supervised classification: The effect of learning task on conceptual flexibility.

Hoffman¹,

Rehder²

2010

Journal of Experimental Psychology: General

104

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Research has shown that learning a concept via standard supervised classification leads to a focus on diagnostic features, whereas learning by inferring missing features promotes the acquisition of withincategory information. Accordingly, we predicted that classification learning would produce a deficit in people's ability to draw novel contrasts-distinctions that were not part of training-compared with feature inference learning. Two experiments confirmed that classification learners were at a disadvantage at making novel distinctions. Eye movement data indicated that this conceptual inflexibility was due to (a) a narrower attention profile that reduces the encoding of many category features and (b) learned inattention that inhibits the reallocation of attention to newly relevant information. Implications of these costs of supervised classification learning for views of conceptual structure are discussed.

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“…Chen Hegdé, Fang, Murray, & Kersten, 2008;Hegdé, Thompson, Brady, & Kersten, 2012), as well as experience with learning the important and 'informative' features to focus on (Blair, Watson, & Meier, 2009;Blair, Watson, Walshe, & Maj, 2009;L. Chen, Meier, Blair, Watson, & Wood, 2013).…”

Section: Discussionmentioning

confidence: 99%

The influence of experience upon information-sampling and decision-making behaviour during risk assessment in military personnel

et al. 2015

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We examined the influence of experience upon information-sampling and decisionmaking behaviour in a group of military personnel as they conducted risk assessments of scenes photographed from patrol routes during the recent conflict in Afghanistan. Their risk assessment was based on an evaluation of Potential Risk Indicators during examination of each scene. We found that both participant groups were equally likely to fixate Potential Risk Indicators, demonstrating similarity in the selectivity of their information-sampling. However, the inexperienced participants made more revisits to Potential Risk Indicators, had longer response times, and were more likely to decide that the scenes contained a high level of risk. Together, these results suggest that experience primarily modulates decision-making behaviour. We discuss potential routes to train personnel to conduct risk assessments in a more similar manner to experienced participants.Acknowledgements:

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Errors, efficiency, and the interplay between attention and category learning

Cited by 47 publications

References 38 publications

How prior knowledge affects selective attention during category learning: An eyetracking study

How prior knowledge affects selective attention during category learning: An eyetracking study

The costs of supervised classification: The effect of learning task on conceptual flexibility.

The influence of experience upon information-sampling and decision-making behaviour during risk assessment in military personnel

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