Effects of category diversity on learning, memory, and generalization

Hahn, Ulrike; Bailey, Todd M.; Elvin, Lucy Brenda Clare

doi:10.3758/bf03195318

Cited by 48 publications

(64 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…especially if those members are outside the range of the trained category (e.g., Cohen, Nosofky, & Zaki, 2001;Hahn et al, 2005). Our results advance these result by showing that categorical training variability helps in generalising to novel members of a novel category.…”

Section: Discussionsupporting

confidence: 78%

“…For our results, this means that training variability enhances the cognitive processes in a way that more encompassing categories are created. This is a possibility given the current evidence that variable categories help in generalising to members that are outside the range of the trained category but belong to the same category (e.g., Cohen, Nosofsky, & Zaki, 2001;Hahn, Bailey, & Elvin, 2005). Thus, the benefit of training variability would hold if we use novel items from a well-known threat category at transfer (e.g., Tools).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Diversity during training enhances detection of novel stimuli

González

Madhavan

2011

Journal of Cognitive Psychology

View full text Add to dashboard Cite

This research demonstrates that when individuals are expected to detect novel targets, they will be best prepared when trained with diverse categories. Participants were trained in a simulated luggage screening task, in one of three conditions of diversity: high (participants searched for dangerous objects belonging to five different categories); low (participants searched for targets belonging to one of the five categories); and no training (control condition). After training, all participants were asked to look for the same novel dangerous objects in the bags. Results show that, during training, the low diversity condition resulted in highest hit rates and fastest response times. In contrast, after training, results were reversed: participants that trained in a high diversity condition were most effective at detecting novel targets. Those with no training at all were equally poor at detecting novel targets as those that trained in a low diversity condition.

show abstract

Section: Discussionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Diversity during training enhances detection of novel stimuli

González

Madhavan

2011

Journal of Cognitive Psychology

View full text Add to dashboard Cite

show abstract

“…The counterintuitiveness of this result may reflect a general failure to appreciate the cognitive benefits of diversity, a failure that may also explain the results of Experiments 3 and 4. But before drawing too bleak a conclusion from our results, it should be pointed out that they clash with a large literature showing that adults and even children routinely take diversity into account in a variety of tasks (see, for instance, Hahn, Bailey, & Elvin, 2005;Osherson, Smith, Wilkie & Lopez, 1990;Heit & Hahn, 2001). A possible explanation for our discrepant findings is that participants may have inferred that when the audience was more diverse, the scope of the arguments was wider, which would make the expertise of the various audience members potentially less relevant to the evaluation of the argument.…”

Section: Resultscontrasting

confidence: 39%

Evaluating arguments from the reaction of the audience

Mercier¹,

Strickland²

2012

Thinking & Reasoning

View full text Add to dashboard Cite

In studying how lay people evaluate arguments, psychologists have typically focused on logical form and content. This emphasis has masked an important yet underappreciated aspect of everyday argument evaluation: social cues to argument strength. Here we focus on the ways in which observers evaluate arguments by the reaction they evoke in an audience. This type of evaluation is likely to occur either when people are not privy to the content of the arguments or when they are not expert enough to appropriately evaluate it. Four experiments explore cues that participants might take into account in evaluating arguments from the reaction of the audience. They demonstrate that participants can use audience motivation, expertise, and size as clues to argument quality. By contrast we find no evidence that participants take audience diversity into account. In press Thinking and Reasoning Abstract.In studying how lay people evaluate arguments, psychologists have typically focused on logical form and content. This emphasis has masked an important yet underappreciated aspect of every day argument evaluation: social cues to argument strength. Here, we focus on the ways in which observers evaluate arguments by the reaction they evoke in an audience. This type of evaluation is likely to occur either when people are not privy to the content of the arguments or when they are not expert enough to appropriately evaluate it. Four experiments explore cues that participants might take into account in evaluating arguments from the reaction of the audience. They demonstrate that participants can use audience motivation, expertise and size as clues to argument quality. By contrast, we find no evidence that participants take audience diversity into account.Keywords: argument evaluation, argumentation, audience, social cues.Arguments can be evaluated in several ways. Typically, their form and content is the subject of scrutiny. Their logical validity can be assessed, and this has been the topic of logic. Their content also matters: minimally, if the premises are known to be false, the argument loses its appeal. Straddling form and content, argumentation schemes-appeal to authority, argument from example, etc. Most attention in experimental psychology has focused on the first way to evaluate arguments. The psychology of reasoning has mostly focused on testing people's ability to detect the logical validity of arguments, or to follow other normative guidelines such as Bayes' rule (Evans, 2002;Hahn & Oaksford, 2007). Studies of persuasion and attitude change have evaluated the impact of numerous factors, including the strength of different arguments (Petty & Wegener, 1998). By contrast, little attention has been devoted to the evaluation of arguments by way of the reaction of their intended audience.Yet we are often unable to evaluate the form or content of arguments. In some cases, we are simply not privy to the arguments and the reaction of the audience is the only clue we have. In other cases the arguments are available, but we don...

show abstract

“…What is the source of participants' preference for tight clusters? With both adult and child participants, it is generally the case that more variable categories encourage more liberal category extensions (Hahn et al, 2005;Mareschal et al, 2002;Rips, 1989;Smith & Sloman, 1994;Stewart & Chater, 2002). We can thus speculate that classifications which involve tight clusters are more intuitive exactly because there is less ambiguity about cluster membership.…”

Section: Discussionmentioning

confidence: 99%

Measuring category intuitiveness in unconstrained categorization tasks

et al. 2011

Self Cite

View full text Add to dashboard Cite

This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractWhat makes a category seem natural or intuitive? In this paper, an unsupervised categorization task was employed to examine observer agreement concerning the categorization of nine different stimulus sets. The stimulus sets were designed to capture different intuitions about classification structure. The main empirical index of category intuitiveness was the frequency of the preferred classification, for different stimulus sets.With 169 participants, and a within participants design, with some stimulus sets the most frequent classification was produced over 50 times and with others not more than two or three times. The main empirical finding was that cluster tightness was more important in determining category intuitiveness, than cluster separation. The results were considered in relation to the following models of unsupervised categorization: DIVA, the rational model, the simplicity model, SUSTAIN, an unsupervised version of the generalized context model (UGCM), and a simple geometric model based on similarity. DIVA, the geometric approach, SUSTAIN, and the UGCM provided good, though not perfect, fits. Overall, the present work highlights several theoretical and practical issues regarding unsupervised categorization and reveals weaknesses in some of the corresponding formal models.

show abstract

Effects of category diversity on learning, memory, and generalization

Cited by 48 publications

References 41 publications

Diversity during training enhances detection of novel stimuli

Diversity during training enhances detection of novel stimuli

Evaluating arguments from the reaction of the audience

Measuring category intuitiveness in unconstrained categorization tasks

Contact Info

Product

Resources

About