Alignment effects on learning multiple, use-relevant classification systems

Sifonis, Cynthia M.; Ross, Brian H.

doi:10.3758/bf03194332

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…(b) Although inference learning does not lead people to learn which feature values distinguish the categories, people often make inferences about dimensions that have contrasting values across categories. There is some evidence that people prefer to organize categories around a common set of dimensions with contrasting values (Billman, 1996; Billman & Dávila, 2001; Sifonis & Ross, 2002). People are most likely to have to answer inference questions about the values of features on these salient dimensions.…”

Section: Inference and Classificationmentioning

confidence: 99%

Category use and category learning.

Markman¹,

Ross²

2003

Psychological Bulletin

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303

298

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Categorization models based on laboratory research focus on a narrower range of explanatory constructs than appears necessary for explaining the structure of natural categories. This mismatch is caused by the reliance on classification as the basis of laboratory studies. Category representations are formed in the process of interacting with category members. Thus, laboratory studies must explore a range of category uses. The authors review the effects of a variety of category uses on category learning. First, there is an extensive discussion contrasting classification with a predictive inference task that is formally equivalent to classification but leads to a very different pattern of learning. Then, research on the effects of problem solving, communication, and combining inference and classification is reviewed.

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Section: Inference and Classificationmentioning

confidence: 99%

Category use and category learning.

Markman¹,

Ross²

2003

Psychological Bulletin

Self Cite

303

298

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show abstract

“…This result is very robust and has been found with a variety of materials (e.g., spy codes, bank loans, fictional animals), dependent measures (e.g., generation, frequency judgments), and variations in paradigms (Ross, 1997(Ross, ,1999(Ross, , 2000Sifonis & Ross, 2002). The finding occurs even with young children (Ross, Gelman, & Rosengren, in press) and when the relevant knowledge is relational and even abstract (Ross & Warren, 2002).…”

Section: Category Learning Is Not Just Learning To Classifymentioning

confidence: 57%

Beyond classification learning.

Ross¹,

Chin-Parker²,

Diaz³

Categorization Inside and Outside the Laboratory: Essays in Honor of Douglas L. Medin.

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For the last 25 years, Douglas Medin has been one of the leading researchers in the domain of categories. He has also been quite influential in the field, and much of the first author's thinking about categories began when the first author was a new faculty member at the University of Illinois with an office next to Professor Medin's (with a brief switch to the first person for ease of reading). Medin was a great mentor (and still is), and he offered to read everything I wrote and comment on it. It was wonderful to get expert advice on my writing and thinking. In my exuberance (I was young), I offered to reciprocate, to read and comment on everything he wrote. Well, it did not take me long to discover that he was writing about 10 times as much as I was. However, given the quality of the comments, I think I still came out ahead. In addition, I had a chance to read and discuss his work with him (plus, I realize now that he was not giving me everything he was writing). I still find myself sometimes including points or ways of expressing something that I can trace back to the comments Medin gave me. Most important, he questioned everything. I would often give him background on a problem I was thinking about, explain my ideas, design, and predictions. He would listen politely and then ask whether a basic assumption of mine (and the field's) might be wrong. He might say, "Yes, that sounds good, or maybe it is that . . ." and then question the point I had begun with. It would drive me crazy, but eventually I think I understood his "suggestion" about how to approach a research topic. This chapter is one attempt to see if I did.Categories are critical for a wide variety of cognitive activities, such as classification, inference, problem solving, explanation, and communication. Thus an understanding of categories is a critical part of understanding cognition. The goal of this chapter is to examine a central aspect of the study of category learning, classification learning, and reconsider its role.We thank the editors of this volume for their wonderful organization of the festschrift. We were helped greatly by the comments of Art Markman and Gregory Murphy. Last, but not least, we thank Douglas Medin for his influence and friendship.

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Consistent Contrast and Correlation in Free Sorting

Billman¹,

Davies²

2005

The American Journal of Psychology

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Two experiments investigated free sorting, a type of unsupervised learning, with multiattribute drawings of alien animals. In previous research on concept formation, with simpler stimulus structure than ours, participants were insensitive to correlational structure in the stimuli, producing primarily "1D sorts," based on the values ofjust 1 dimension or attribute. Our experiments showed that participants used many strategies in categorizing but preferred to generate groupings that reflected the correlations in input when this did not violate consistent contrast. The second experiment used hierarchically structured stimuli to show that participants’ sort strategies favor consistency within a set of contrasting categories, distinct from any preference for 1D sorting. Finally, both experiments show that correlational sorts are much more likely when the correlation-based sort contrasts consistently. Our data show complexity at work in free sort tasks: People are sensitive to multiple and sometimes conflicting biases for consistency and correlational structure in the category systems they create.

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Alignment effects on learning multiple, use-relevant classification systems

Cited by 3 publications

References 13 publications

Category use and category learning.

Category use and category learning.

Beyond classification learning.

Consistent Contrast and Correlation in Free Sorting

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