Comparison in the Development of Categories

Recent research on children's word learning has led to a paradox. Although word learning appears to be a deep source of insight into conceptual knowledge for children, preschoolers often categorize objects on the basis of shallow perceptual features such as shape. The current studies seek to resolve this discrepancy. We suggest that comparing multiple instances of a category enables children to extract deeper relational commonalities among category members. We examine 4-year-olds' categorization behaviors when asked to select a match for a target object (e.g., an apple) between a perceptually similar, out-of-kind object (e.g., a balloon) and a perceptually different category match (e.g., a banana). Children who learn a novel word as a label for multiple instances of the category are more likely to select the category match over the perceptual match. Children who learn a label for only one instance are equally likely to select either alternative. This effect is present even when individual target instances are more perceptually similar to the perceptual choice than to the category choice. We conclude that structural alignment processes may be important in the development of category understanding.     

The development of category learning strategies: What makes the difference?

Category learning can be achieved by identifying common features among category members, distinctive features among non-members, or both. These processes are psychologically and computationally distinct, and may have implications for the acquisition of categories at different hierarchical levels. The present study examines an account of children’s difficulty in acquiring categories at the subordinate level grounded on these distinct comparison processes. Adults and children performed category learning tasks in which they were exposed either to pairs of objects from the same novel category or pairs of objects from different categories. The objects were designed so that for each category learning task, two features determined category membership whereas two other features were task irrelevant. In the learning stage participants compared pairs of objects noted to be either from the same category or from different categories. Object pairs were chosen so that the objective amount of information provided to the participants was identical in the two learning conditions. We found that when presented only with object pairs noted to be from the same category, young children (6 ? YO ? 9.5) learned the novel categories just as well as older children (10 ? YO ? 14) and adults. However, when presented only with object pairs known to be from different categories, unlike older children and adults, young children failed to learn the novel categories. We discuss cognitive and computational factors that may give rise to this comparison bias, as well as its expected outcomes.     

Children learn words easier when they are interested in the category to which the word belongs

The overall pattern of vocabulary development is relatively similar across children learning different languages. However, there are considerable differences in the words known to individual children. Historically, this variability has been explained in terms of differences in the input. Here, we examine the alternate possibility that children's individual interest in specific natural categories shapes the words they are likely to learn – a child who is more interested in animals will learn a new animal name easier relative to a new vehicle name. Two‐year‐old German‐learning children (N = 39) were exposed to four novel word–object associations for objects from four different categories. Prior to the word learning task, we measured their interest in the categories that the objects belonged to. Our measure was pupillary change following exposure to familiar objects from these four categories, with increased pupillary change interpreted as increased interest in that category. Children showed more robust learning of word–object associations from categories they were more interested in relative to categories they were less interested in. We further found that interest in the novel objects themselves influenced learning, with distinct influences of both category interest and object interest on learning. These results suggest that children's interest in different natural categories shapes their word learning. This provides evidence for the strikingly intuitive possibility that a child who is more interested in animals will learn novel animal names easier than a child who is more interested in vehicles.     

Categorization in infancy: labeling induces a persisting focus on commonalities

Recent studies with infants and adults demonstrate a facilitative role of labels in object categorization. A common interpretation is that labels highlight commonalities between objects. However, direct evidence for such a mechanism is lacking. Using a novel object category with spatially separate features that are either of low or high variability across the stimulus set, we tracked 12‐month‐olds’ attention to object features during learning and at test. Learning occurred in both conditions, but what was learned depended on whether or not labels were heard. A detailed analysis of eye movements revealed that infants in the two conditions employed different object processing strategies. In the silent condition, looking patterns were governed exclusively by the variability of object parts. In the label condition, infants’ categorization performance was linked to their relative attention to commonalities. Moreover, the commonality focus persisted after learning even in the absence of labels. These findings constitute the first experimental evidence that labels induce a persistent focus on commonalities.     

A little labeling goes a long way: Semi‐supervised learning in infancy

There is considerable evidence that labeling supports infants' object categorization. Yet in daily life, most of the category exemplars that infants encounter will remain unlabeled. Inspired by recent evidence from machine learning, we propose that infants successfully exploit this sparsely labeled input through “semi‐supervised learning.” Providing only a few labeled exemplars leads infants to initiate the process of categorization, after which they can integrate all subsequent exemplars, labeled or unlabeled, into their evolving category representations. Using a classic novelty preference task, we introduced 2‐year‐old infants (n = 96) to a novel object category, varying whether and when its exemplars were labeled. Infants were equally successful whether all exemplars were labeled (fully supervised condition) or only the first two exemplars were labeled (semi‐supervised condition), but they failed when no exemplars were labeled (unsupervised condition). Furthermore, the timing of the labeling mattered: when the labeled exemplars were provided at the end, rather than the beginning, of familiarization (reversed semi‐supervised condition), infants failed to learn the category. This provides the first evidence of semi‐supervised learning in infancy, revealing that infants excel at learning from exactly the kind of input that they typically receive in acquiring real‐world categories and their names.     

Unsupervised categorization with a child sample: category cohesion development

Studies into categorization have demonstrated that the ability to form concepts is an essential ability in cognitive development. For example, before a decision about anything can be made, firstly category concepts need to be acquired in order to make efficient decisions about that situation. The present study explored a particular type of category learning, not previously explored in this particular context – unsupervised categorization with 16 items and two dimensions, and comparing specifically children vs. adults. Previous studies have typically focused on simpler designs such as three items of two dimensions in the triad tasks, or a greater number of dimensions but with much fewer items per category in other unsupervised settings. This study investigated unsupervised categorization with two levels of task difficulty, and compared two different populations, children and adults. The findings revealed that adults performed better for the easy condition but there was no difference between these groups for the more difficult category task. The findings also revealed that unsupervised categorization in more complex settings result in more one dimensional sorting, for both children and adults. The results are discussed in the context of unsupervised categorization development abilities in children.     

Incidental learning in a multisensory environment across childhood

Multisensory information has been shown to modulate attention in infants and facilitate learning in adults, by enhancing the amodal properties of a stimulus. However, it remains unclear whether this translates to learning in a multisensory environment across middle childhood, and particularly in the case of incidental learning. One hundred and eighty‐one children aged between 6 and 10 years participated in this study using a novel Multisensory Attention Learning Task (MALT). Participants were asked to respond to the presence of a target stimulus whilst ignoring distractors. Correct target selection resulted in the movement of the target exemplar to either the upper left or right screen quadrant, according to category membership. Category membership was defined either by visual‐only, auditory‐only or multisensory information. As early as 6 years of age, children demonstrated greater performance on the incidental categorization task following exposure to multisensory audiovisual cues compared to unisensory information. These findings provide important insight into the use of multisensory information in learning, and particularly on incidental category learning. Implications for the deployment of multisensory learning tasks within education across development will be discussed.     

Knowledge Structures and Linear Separability: Integrating Information in Object and Social Categorization

These experiments were designed to determine if the naturalness of abstract category structures varies with content domain. Specifically, the degree to which linear separability constrains categorization was investigated in object and social domains. Linearly separable (LS) categories are categories that can be perfectly partitioned on the basis of a weighted, additive combination of component information. Across a wide variety of stimulus materials and classification tasks LS structures were found to be more compatible with social than object materials. In sorting tasks, participants were more likely to sum characteristic features and form LS categories with social materials. In learning tasks, LS structures were easier to learn with social materials but nonlinearly separable structures were easier to learn with object materials. This interaction between category structure and content domain was attributed to differences in the types of knowledge and integration strategies that were activated. In object conditions, strategies that were inconsistent with adding independent features were observed (e.g., focusing on single dimensions, using configural properties, and relying on analogy). In social conditions, however, summing the evidence and learning LS structures appeared to be a natural strategy. It was concluded that the structure of knowledge varies with domain, and consequently it will be difficult to formulate domain general constraints in terms of abstract structural properties such as linear separability. Differences between object and social categorization systems are discussed.     

非监控类别学习的分类策略与表征

类别学习是人类对不同类别加以归类的过程。类别信息的表征、分类策略运用的特点一直是类别学习研究的重点。非监控类别学习可分为直接的非监控类别学习和间接的非监控类别学习。直接的非监控类别学习(非限制任务, 限制任务)中被试的分类策略具有分类“单维度倾向”策略特点,类别变异程度会影响类别表征; 间接的非监控类别学习更倾向形成相似性表征, 直接的非监控类别学习则为基于规则表征。现有的非监控类别学习的理论对分类策略和表征的解释仍显薄弱, 不同学习任务下类别迁移和知识效应的研究还存在不足, 未来研究还需要进一步验证知识效应对非监控类别学习的认知加工过程的影响、探索影响类别表征形成的因素等问题。     

Whichever way you choose to categorize, working memory helps you learn

There has been growing interest in the relationship between the capacity of a person's working memory and their ability to learn to categorize stimuli. While there is evidence that working memory capacity (WMC) is related to the speed of category learning, it is unknown whether WMC predicts which strategies people use when there are multiple possible solutions to a categorization problem. To explore the relationship between WMC, category learning, and categorization strategy use, 173 participants completed two categorization tasks and a battery of WMC tasks. WMC predicted the speed of category learning, but it did not predict which strategies participants chose to perform categorization. Thus, WMC does not predict which categorization strategies people use but it predicts how well they will use the strategy they select.     

Perceptual Learning of Intonation Contour Categories in Adults and 9‐ to 11‐Year‐Old Children: Adults Are More Narrow‐Minded

We report on rapid perceptual learning of intonation contour categories in adults and 9‐ to 11‐year‐old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: Previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age‐related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour, while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail‐end of the developmental trajectory for learning intonation contour categories: There is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult‐like.     

Word Learning and Attention Allocation Based on Word Class and Category Knowledge

Attention allocation in word learning may vary developmentally based on the novelty of the object. It has been suggested that children differentially learn verbs based on the novelty of the agent, but adults do not because they automatically infer the object's category and thus treat it like a familiar object. The current research examined whether adults and children differentially learn words or attend to objects without access to category knowledge in a relatively difficult (Experiment 1, adult n = 54, child n = 66) and a relatively easy task (Experiment 2, adult n = 88, child n = 62). Results show that category knowledge affects noun and verb extension for children but not adults and that adults similarly attended to objects when learning a verb regardless of category knowledge. These findings highlight the importance of investigating how word class, attention allocation, and categorical inference interact across development. Copyright © 2014 John Wiley & Sons, Ltd.     

Whichever way you choose to categorize,working memory helps you learn

There has been growing interest in the relationship between the capacity of a person's working memory and their ability to learn to categorize stimuli. While there is evidence that working memory capacity (WMC) is related to the speed of category learning, it is unknown whether WMC predicts which strategies people use when there are multiple possible solutions to a categorization problem. To explore the relationship between WMC, category learning, and categorization strategy use, 173 participants completed two categorization tasks and a battery of WMC tasks. WMC predicted the speed of category learning, but it did not predict which strategies participants chose to perform categorization. Thus, WMC does not predict which categorization strategies people use but it predicts how well they will use the strategy they select.     

Evidence for a form of mutual exclusivity during label acquisition by grey parrots (Psittacus erithacus)?

The authors present context-dependent evidence for a form of mutual exclusivity during label learning by Grey parrots (Psittacus erithacus). For human children, mutual exclusivity refers to their assumption during early word learning that an object has one and only one label. Along with the whole-object assumption (that a label likely refers to an entire object rather than some partial aspect), mutual exclusivity is thought to guide children in initial label acquisition. It may also help children overcome the whole-object assumption by helping them interpret a novel word as something other than an object label, but for young children, any second label for an object can initially be more difficult to acquire than the first. The authors show that Grey parrots quickly learn object labels for items, then have considerable difficulty learning to use color labels with respect to a previously labeled item unless specifically taught to use a color and object label as a pair.     

不同学习方式下归类不确定时的特征推理

采用学习-迁移模式, 探讨了同时学习和继时学习两种方式下归类不确定时的特征推理。共包括2个实验, 其中实验1探讨了固定学习轮次的情况, 实验2探讨了固定学习正确率的情况。实验结果表明：同时呈现类别要素的同时学习方式下, 被试习得序列式的单类别表征(原型表征), 在归类不确定时的特征推理中按照“单类的Bayesian规则”进行特征推理, 即P(j\F) =P(k\F)·P(j\k); 相继呈现类别要素的继时学习方式下, 被试习得并列式的多类别表征, 在归类不确定时的特征推理中按照“理性模型”进行推理, 即 P(j\F) =Σk P(k\F)·P(j\k)。     

Working memory capacity and categorization: individual differences and modeling

Working memory is crucial for many higher-level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization, and modeling in category learning has thus far been largely uninformed by knowledge about people's memory processes. This article reports a large study (N = 113) that related people's working memory capacity (WMC) to their category-learning performance using the 6 problem types of Shepard, Hovland, and Jenkins (1961). Structural equation modeling revealed a strong relationship between WMC and category learning, with a single latent variable accommodating performance on all 6 problems. A model of categorization (the Attention Learning COVEring map, ALCOVE; Kruschke, 1992) was fit to the individual data and a single latent variable was sufficient to capture the variation among associative learning parameters across all problems. The data and modeling suggest that working memory mediates category learning across a broad range of tasks.     

Learning rule-described and non-rule-described categories: a comparison of children and adults

Three experiments investigated the ability of 3-, 5-, and 8-year-old children as well as adults to learn sets of perceptual categories. Adults and children performed comparably on categories that could be learned by either a single-dimensional rule or by associative learning mechanisms. However, children showed poorer performance relative to adults in learning categories defined by a disjunctive rule and categories that were nonlinearly separable. Increasing the task demands for adults resulted in child-like performance on the disjunctive categories. Decreasing the task demands for children resulted in more adult-like performance on the disjunctive categories. The authors interpret these results within a multiple-systems approach to category learning and suggest that children have not fully developed the same explicit category learning system as adults.     

Selective social learning in infancy: looking for mechanisms

Although there is mounting evidence that selective social learning begins in infancy, the psychological mechanisms underlying this ability are currently a controversial issue. The purpose of this study is to investigate whether theory of mind abilities and statistical learning skills are related to infants’ selective social learning. Seventy‐seven 18‐month‐olds were first exposed to a reliable or an unreliable speaker and then completed a word learning task, two theory of mind tasks, and a statistical learning task. If domain‐general abilities are linked to selective social learning, then infants who demonstrate superior performance on the statistical learning task should perform better on the selective learning task, that is, should be less likely to learn words from an unreliable speaker. Alternatively, if domain‐specific abilities are involved, then superior performance on theory of mind tasks should be related to selective learning performance. Findings revealed that, as expected, infants were more likely to learn a novel word from a reliable speaker. Importantly, infants who passed a theory of mind task assessing knowledge attribution were significantly less likely to learn a novel word from an unreliable speaker compared to infants who failed this task. No such effect was observed for the other tasks. These results suggest that infants who possess superior social‐cognitive abilities are more apt to reject an unreliable speaker as informant. A video abstract of this article can be viewed at: https://youtu.be/zuuCniHYzqo     

Working memory does not dissociate between different perceptual categorization tasks

Working memory is crucial for many higher level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization. This article reports 2 studies that related people's working memory capacity (WMC) to their learning performance on multiple rule-based and information-integration perceptual categorization tasks. In both studies, structural equation modeling revealed a strong relationship between WMC and category learning irrespective of the requirement to integrate information across multiple perceptual dimensions. WMC was also uniformly related to people's ability to focus on the most task-appropriate strategy, regardless of whether or not that strategy involved information integration. Contrary to the predictions of the multiple systems view of categorization, working memory thus appears to underpin performance in both major classes of perceptual category-learning tasks.     

Compensatory processing during rule-based category learning in older adults

Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer’s or Parkinson’s disease. To further investigate aging’s effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one’s behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.