Category learning in the context of co-presented items

Andrews, Janet K.; Livingston, Kenneth R.; Kurtz, Kenneth J.

doi:10.1007/s10339-010-0377-5

Cited by 19 publications

(23 citation statements)

References 49 publications

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“…Such a conclusion follows other research on the influence of item juxtapositions on learning (Hammer et al, 2009; Andrews et al, 2011). This would support the idea that there is a tendency for humans and animals to readily group together things that look alike (Urcuioli, 2001).…”

Section: Discussionsupporting

confidence: 89%

Similarity-Dissimilarity Competition in Disjunctive Classification Tasks

Mathy¹,

Haladjian²,

Laurent³

et al. 2013

Front. Psychology

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Typical disjunctive artificial classification tasks require participants to sort stimuli according to rules such as “x likes cars only when black and coupe OR white and SUV.” For categories like this, increasing the salience of the diagnostic dimensions has two simultaneous effects: increasing the distance between members of the same category and increasing the distance between members of opposite categories. Potentially, these two effects respectively hinder and facilitate classification learning, leading to competing predictions for learning. Increasing saliency may lead to members of the same category to be considered less similar, while the members of separate categories might be considered more dissimilar. This implies a similarity-dissimilarity competition between two basic classification processes. When focusing on sub-category similarity, one would expect more difficult classification when members of the same category become less similar (disregarding the increase of between-category dissimilarity); however, the between-category dissimilarity increase predicts a less difficult classification. Our categorization study suggests that participants rely more on using dissimilarities between opposite categories than finding similarities between sub-categories. We connect our results to rule- and exemplar-based classification models. The pattern of influences of within- and between-category similarities are challenging for simple single-process categorization systems based on rules or exemplars. Instead, our results suggest that either these processes should be integrated in a hybrid model, or that category learning operates by forming clusters within each category.

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Section: Discussionsupporting

confidence: 89%

Similarity-Dissimilarity Competition in Disjunctive Classification Tasks

Mathy¹,

Haladjian²,

Laurent³

et al. 2013

Front. Psychology

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“…In the context of geology instruction, for example, Jee, Uttal, and Gentner (2008) demonstrated that studying two highly similar examples that differ only in terms of the presence of a Bfault^improves learning of that concept. In a triad-presentation method, Andrews, Livingston, and Kurtz (2011) found that presenting members of three separate categories simultaneously on each trial led to better learning than presenting three members of the same category.…”

Section: Electronic Supplementary Materialsmentioning

confidence: 99%

Organized simultaneous displays facilitate learning of complex natural science categories

et al. 2017

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Subjects learned to classify images of rocks into the categories igneous, metamorphic, and sedimentary. In accord with the real-world structure of these categories, the to-beclassified rocks in the experiments had a dispersed similarity structure. Our central hypothesis was that learning of these complex categories would be improved through observational study of organized, simultaneous displays of the multiple rock tokens. In support of this hypothesis, a technique that included the presentation of the simultaneous displays during phases of the learning process yielded improved acquisition (Experiment 1) and generalization (Experiment 2) compared to methods that relied solely on sequential forms of study and testing. The technique appears to provide a good starting point for application of cognitive-psychology principles of effective category learning to the science classroom.

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“…In one line of work (Andrews, Livingston, & Kurtz, 2011), learners were given the opportunity to compare a target item to two co-presented context items during each trial of a classification learning task based on three categories and continuous valued dimensions. It is a natural prediction that comparison of same-category items ought to promote a generative learning style in the sense of using the comparison opportunity to help discover the commonalities shared by members of each category.…”

Section: Alternatives To Learning Categories One Example At a Timementioning

confidence: 99%