Concept and Category Learning in Humans

Ross, Brian H.; Taylor, Eric; Middleton, Erica L.; Nokes, Timothy J.

doi:10.1016/b978-012370509-9.00139-x

Cited by 10 publications

(7 citation statements)

References 88 publications

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“…Reviews and overviews of the field (Goldstone & Kersten, 2003;Kurtz, 2007;Love, Medin, & Gureckis, 2004;Markman & Ross, 2003;Murphy, 2002;Ross, Taylor, Middleton, & Nokes, 2008;Solomon, Medin, & Lynch, 1999;Wills & Pothos, 2012) collectively highlight directions where progress is needed: (1) addressing the set of distinct and somewhat contradictory psychological constructs that have been shown to exhibit explanatory power; and (2) extending behavioral studies and modeling work to address a broader and more naturalistic view of category learning. Regarding the first challenge, the field offers a considerable collection of powerful explanatory constructs implemented in mechanistic models of category learning such as: dimensional selective attention, multiplicative similarity, exemplar storage, error-driven learning, hypothesis testing via explicit rules, decision bounds, abstraction of prototypes or clusters, and theory-like prior knowledge.…”

Section: Traditional Artificial Classification Learningmentioning

confidence: 99%

Human Category Learning: Toward a Broader Explanatory Account

Kurtz

2015

Psychology of Learning and Motivation

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Section: Traditional Artificial Classification Learningmentioning

confidence: 99%

Human Category Learning: Toward a Broader Explanatory Account

Kurtz

2015

Psychology of Learning and Motivation

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“…By contrast, Type IV is linearly separable and embodies a rudimentary form of the family resemblance organization prevalent in natural categories (Rosch & Mervis, 1975). At the theoretical level, the traditional Type II advantage over Type IV (supported by findings such as in Medin & Schwanenflugel, 1981) has contributed to increased acceptance of exemplar-based models (along with certain other models discussed below) and a decline of the prototype view among researchers who focus on the phenomenology and modeling of artificial classification learning (see the following reviews: Murphy, 2002;Ross, Taylor, Middleton, & Nokes, 2008).…”

Section: Impact Of the Traditional Shj Ordering On The Psychology Of ...mentioning

confidence: 99%

Human learning of elemental category structures: Revising the classic result of Shepard, Hovland, and Jenkins (1961).

Kurtz¹,

Levering²,

Stanton³

et al. 2013

Journal of Experimental Psychology: Learning, Memory, and Cogni

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The findings of Shepard, Hovland, and Jenkins (1961) on the relative ease of learning 6 elemental types of 2-way classifications have been deeply influential 2 times over: 1st, as a rebuke to pure stimulus generalization accounts, and again as the leading benchmark for evaluating formal models of human category learning. The litmus test for models is the ability to simulate an observed advantage in learning a category structure based on an exclusive-or (XOR) rule over 2 relevant dimensions (Type II) relative to category structures that have no perfectly predictive cue or cue combination (including the linearly-separable Type IV). However, a review of the literature reveals that a Type II advantage over Type IV is found only under highly specific experimental conditions. We investigate when and why a Type II advantage exists to determine the appropriate benchmark for models and the psychological theories they represent. A series of 8 experiments link particular conditions of learning to outcomes ranging from a traditional Type II advantage to compelling non-differences and reversals (i.e., Type IV advantage). Common interpretations of the Type II advantage as either a broad-based phenomenon of human learning or as strong evidence for an attention-mediated similarity-based account are called into question by our findings. Finally, a role for verbalization in the category learning process is supported.

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“…Comparison and categorization are two of the core mechanisms that underlie human learning, understanding, and reasoning. Yet for the most part, they have been studied quite separately (for reviews, see Gentner, Holyoak, & Kokinov, 2001;Gentner & Markman, 1997;Holyoak & Thagard, 1995;Levering & Kurtz, 2010;Murphy, 2002;Ross, Taylor, Middleton, & Nokes, 2008). In the study of categorization, much research has focused on the classification learning paradigm-across a series of trials the learner is visually presented with an item drawn from a training set, then a response is made by choosing which category the item belongs to, and corrective feedback is received.…”

mentioning

confidence: 99%

Comparison promotes learning and transfer of relational categories.

Kurtz¹,

Boukrina²,

Gentner³

2013

Journal of Experimental Psychology: Learning, Memory, and Cogni

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We investigated the effect of co-presenting training items during supervised classification learning of novel relational categories. Strong evidence exists that comparison induces a structural alignment process that renders common relational structure more salient. We hypothesized that comparisons between exemplars would facilitate learning and transfer of categories that cohere around a common relational property. The effect of comparison was investigated using learning trials that elicited a separate classification response for each item in presentation pairs that could be drawn from the same or different categories. This methodology ensures consideration of both items and invites comparison through an implicit same-different judgment inherent in making the two responses. In a test phase measuring learning and transfer, the comparison group significantly outperformed a control group receiving an equivalent training session of single-item classification learning. Comparison-based learners also outperformed the control group on a test of far transfer, that is, the ability to accurately classify items from a novel domain that was relationally alike, but surface-dissimilar, to the training materials. Theoretical and applied implications of this comparison advantage are discussed.

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Concept and Category Learning in Humans

Cited by 10 publications

References 88 publications

Human Category Learning: Toward a Broader Explanatory Account

Human Category Learning: Toward a Broader Explanatory Account

Human learning of elemental category structures: Revising the classic result of Shepard, Hovland, and Jenkins (1961).

Comparison promotes learning and transfer of relational categories.

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