Anna V. Fisher

Induction and Categorization in Young Children: A Similarity-Based Model.

The authors present a similarity-based model of induction and categorization in young children (SINC). The model suggests that (a). linguistic labels contribute to the perceived similarity of compared entities and (b). categorization and induction are a function of similarity computed over perceptual information and linguistic labels. The model also predicts young childrens similarity judgment, induction, and categorization performance under different stimuli and task conditions. Predictions of the model were tested and confirmed in 6 experiments, in which 4- to 5-year-olds performed similarity judgment, induction, and categorization tasks using artificial and real labels (Experiments 1-4) and recognition memory tasks (Experiments 5A and 5B). Results corroborate the similarity-based account of young childrens induction and categorization, and they support both qualitative and quantitative predictions of the model.

When Development and Learning Decrease Memory Evidence Against Category-Based Induction in Children

Inductive inference is crucial for learning: If one learns that a cat has a particular biological property, one could expand this knowledge to other cats. We argue that young children perform induction on the basis of similarity of compared entities, whereas adults may induce on the basis of category information. If different processes underlie induction at different points in development, young children and adults would form different memory traces during induction, and would subsequently have different memory accuracy. Experiment 1 demonstrates that after performing an induction task, 5-year-olds exhibit more accurate memory than adults. Experiment 2 indicates that after 5-year-olds are trained to perform induction in an adultlike manner, their memory accuracy drops to the level of adults. These results, indicating that sometimes 5-year-olds exhibit better memory than adults, support the claim that, unlike adults, young children perform similarity-based rather than category-based induction.

When Looks Are Everything Appearance Similarity Versus Kind Information in Early Induction

The goal of this research was to examine mechanisms underlying early induction—specifically, the relation between induction and categorization. Some researchers argue that even early in development, induction is based on category-membership information, whereas others argue that early induction is based primarily on similarity. Children 4 and 5 years of age participated in two types of tasks: categorization and induction. Both tasks were performed with artificial animal-like categories in which appearance was pitted against category membership. Although the children readily acquired category-membership information and subsequently used this information in categorization tasks, they ignored category membership during the induction task, relying instead on the appearance of items. These results support the idea that early in development, induction is similarity based.

Visual Environment, Attention Allocation, and Learning in Young Children When Too Much of a Good Thing May Be Bad

A large body of evidence supports the importance of focused attention for encoding and task performance. Yet young children with immature regulation of focused attention are often placed in elementary-school classrooms containing many displays that are not relevant to ongoing instruction. We investigated whether such displays can affect children’s ability to maintain focused attention during instruction and to learn the lesson content. We placed kindergarten children in a laboratory classroom for six introductory science lessons, and we experimentally manipulated the visual environment in the classroom. Children were more distracted by the visual environment, spent more time off task, and demonstrated smaller learning gains when the walls were highly decorated than when the decorations were removed.

Attentional learning and flexible induction: how mundane mechanisms give rise to smart behaviors.

Young children often exhibit flexible behaviors relying on different kinds of information in different situations. This flexibility has been traditionally attributed to conceptual knowledge. Reported research demonstrates that flexibility can be acquired implicitly and it does not require conceptual knowledge. In Experiment 1, 4- to 5-year-olds successfully learned different context-predictor contingencies and subsequently flexibly relied on different predictors in different contexts. Experiments 2A and 2B indicated that flexible generalization stems from implicit attentional learning rather than from rule discovery, and Experiment 3 pointed to very limited strategic control over generalization behaviors in 4- to 5-year-olds. These findings indicate that mundane mechanisms grounded in associative and attentional learning may give rise to smart flexible behaviors.

Automatic shifts of attention in the Dimensional Change Card Sort task: Subtle changes in task materials lead to flexible switching

Two experiments tested a hypothesis that reducing demands on executive control in a Dimensional Change Card Sort task will lead to improved performance in 3-year-olds. In Experiment 1, the shape dimension was represented by two dissimilar values (stars and flowers), and the color dimension was represented by two similar values (red and pink). This configuration of stimuli rendered shape more salient than color. In Experiment 2, attentional weights of each dimension value were manipulated by using two versus four values to represent the dimensions of shape and color. The results indicated that increasing saliency of the postswitch dimension (Experiment 1) and reducing attentional weights of individual dimension values (Experiment 2) lead to a marked improvement in the postswitch sorting accuracy in 3-year-olds.

Linguistic labels: Conceptual markers or object features?

Linguistic labels affect inductive generalization; however, the mechanism underlying these effects remains unclear. According to one similarity-based model, SINC (similarity, induction, naming, and categorization), early in development labels are features of objects contributing to the overall similarity of compared entities, with early induction being similarity based. If this is the case, then not only identical but also phonologically similar labels may contribute to the overall similarity and thus to induction. These predictions were tested in a series of experiments with 5-year-olds and adults. In Experiments 1-5 participants performed a label extension task, whereas in Experiment 6 they performed a feature induction task. Results indicate that phonological similarity contributes to early induction and support the notion that for young children labels are features of objects.

Semantic similarity of labels and inductive generalization: Taking a second look

Prior research suggests that preschoolers can generalize object properties based on category information conveyed by semantically-similar labels. However, previous research did not control for co-occurrence probability of labels in natural speech. The current studies re-assessed childrens generalization with semantically-similar labels. Experiment 1 indicated that adults made category-based inferences regardless of co-occurrence probability; however, 4-year-olds generalized with semantically-similar labels that co-occurred in child-directed speech (e.g., bunny-rabbit) but not with non-co-occurring labels (e.g., crocodile-alligator). Experiment 2 indicated that generalization with semantically-similar labels increased gradually between 4- and 6-years of age. These results are discussed in relation to theories of early learning.

Similarity, Induction, Naming, and Categorization (SINC): Generalization or Inductive Reasoning? Reply to Heit and Hayes (2005)

This article is a response to E. Heit and B. K. Hayes’s (2005) comment on the target article “Induction and Categorization in Young Children: A Similarity-Based Model” (V. M. Sloutsky & A. V. Fisher, 2004a). The response discusses points of agreement and disagreement with Heit and Hayes; phenomena predicted by similarity, induction, naming, and categorization (SINC); and relationships between SINC and models of verbal inductive reasoning, as well as contributions and limitations of SINC and directions for future research. Overall, the authors disagree with Heit and Hayes’s analysis of limitations of SINC and with their analysis of SINC in the context of verbal inductive reasoning. At the same time, the authors agree that more research is needed to provide a unified account of similarity, induction, categorization, and recognition.

The Development of Categorization

Abstract The ability to categorize is a ubiquitous property of human cognition. However, despite much progress in understanding how children learn to categorize, several important issues remain highly debated. The central issues in this debate concern the role of perceptual input and the role of linguistic labels in categorization and category learning. This chapter reviews recent evidence bearing on these key issues. Based on this evidence, we suggest that (1) categorization begins with extracting structure from the input based on overlapping perceptual features and attentional weights and (2) development of the ability to selectively attend to some features while ignoring others underlies the learning of abstract concepts and categories.