Early Childhood Developement

What is Special Education? 1

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Pre-Test

1. 1. You can use the terms disability and handicap interchangeably. T/F 2. 2. The history of special education began in Europe. T/F 3. 3. The first American legislation that protected students with disabilities was passed in the 1950s.

T/F 4. 4. All students with disabilities should be educated in special education classrooms. T/F 5. 5. Special education law is constantly reinterpreted. T/F

6. Answers can be found at the end of the chapter.

5 Conceptual Development

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Learning Objectives By the end of this chapter, you should be able to:

• Explain the function of concepts in cognitive development.

• Compare and contrast different theories of conceptual organization.

• Identify the development of perceptual concepts of infants and children.

• Outline the development of children’s concepts of biology from different theoretical perspectives.

• Explain how experience and education contribute to conceptual development.

• Summarize the neural foundation of biological concepts in typically and atypically developing children.

• Describe the development of children’s concepts of spatial cognition and geometry.

Pretest Questions

Pretest Questions

1. Animals that look similar to each other are almost always judged by preschool children to be examples of the same animal concept. T/F

2. Five-year-olds prefer to use the word bird, rather than animal or eagle, when labeling an eagle. T/F

3. Infants show a preference for looking at living things over nonliving things. T/F 4. Children with autism show a preference for looking at human faces. T/F 5. In order to understand geometric concepts, children must receive formal instruction.

T/F

Ms. Serrano, a preschool teacher of 2- to 4-year-olds, took her class on a field trip to a nearby conservation park. Yao, a 4-year-old, excitedly ran up to Serrano, showing her a bug she found on a tree. A number of other children came up to see what the excitement was all about. Yao had many questions about the bug, as did the other children. They wanted to know what kind of bug it was, where its mommy and daddy were, what it ate, did it sleep, how big would it grow, and more. Then Stephen joined the group, holding up a multicolored rock he found in a creek. The children wanted to know if it was gold, if it was worth any money, and where it came from.

At first Serrano thought the children did not know much about bugs or rocks. She thought she had a considerable amount to teach them about science. However, she quickly realized they already knew a lot about both. Their questions suggested they understood that as a living thing, bugs had many of the same characteristics of other living things, such as needing food and rest, whereas rocks did not share those same properties. The children needed specific details to fill in the gaps of their knowledge.

Serrano took this opportunity to teach her students more about biology. She held up the bug and asked, “Who knows what kind of bug this is?” The children shouted out their answers. When she asked about the rock, a boy named Joshua wanted to know how big it would grow. Serrano then recognized that although children had a correct understanding of some concepts, they had a number of misconceptions as well. There were many challenges ahead, and she could not wait to get started.

Questions to Think About

1. How do you think the children learned about the different characteristics of bugs and rocks? Did they learn it by observing other living things and nonliving things? Did their parents teach them? Is it possible that some of their knowledge was innate? Explain your reasoning.

2. How would you use this situation as an opportunity to teach students about science? What are some ways you could address the students’ misconceptions of biology?

Introduction

Introduction What do women, fire, and dangerous things have in common? For speakers of Dyirbal, an Aus- tralian Aboriginal language, they are part of the category of balan. Balan is a classifier word that is used prior to nouns to represent different concepts involving females, water, fire, and fighting. Dyirbal speakers use it to categorize objects in their environment, imposing an orga- nization that makes sense to them (Lakoff, 1987). For instance, if talking about a spear, the speakers would use balan before the word for spear. It is somewhat similar to the marking of some nouns as masculine or feminine in Spanish.

The balan example illustrates that concepts—mental representations of the objects and ideas of the world—can differ across cultures. Despite these differences, concepts are fun- damental to human cognition for people of all cultures. Concepts include animals, numbers, space, time, and more. They help make mental life manageable. In a sense, this entire text is about children’s concepts.

Let us consider a common example that involves the concept of a bird. Understanding this concept allows animals to be classified or categorized as an example of a bird or some other species. Imagine how chaotic or overwhelming thinking would be if every time a bird was encountered it was considered a new object and was not recognized as another example of the bird concept. However, because we can categorize objects as an example of a particular concept, we can make sense of the world. Categories are closely related to concepts but refer to grouping different examples of a concept together.

Imagine being told that biologists have discovered a new bird species in South America. Take a moment and notice what mental image comes to mind.

Did the bird you pictured have feathers and a beak? Did it fly? Even though we were not directly told that the new bird had these characteristics, we expect different exemplars of the same concept to share something in common. This is another advantage of having con- cepts. In addition to aiding in classification, they also allow inferences to be made about a new example.

It is easy to understand that concepts are critical to the education of children and adolescents. Almost everything children learn involves conceptual knowledge. This includes mathemati- cal concepts, scientific concepts, social concepts, and others. Thus, understanding conceptual development has direct implications for education. If teachers know how children represent and define particular concepts and the developmental progression of conceptual knowledge, they can create formal and informal learning opportunities for children. Furthermore, chil- dren can also have misconceptions about some concepts. These misconceptions can provide a starting point for teachers to engage children and bring about conceptual change.

The development of children’s concepts has been explored from many of the theoretical per- spectives described in Chapter 1. These include the Piagetian (constructivism), Vygotskian (social-constructivism), information-processing, and nativism (including core knowledge) approaches. We will touch on all of these perspectives, but emphasize the IP and nativism approaches because they are the focus of much current research. We will examine the devel- opment and organization of concepts, such as concepts of furniture and animals. In addi- tion, we will explore concepts that may reflect foundational core domains identified by core

Section 5.1Theories of Concepts

knowledge theory, such as biology and geometry, because of their relevance to education— particularly to science education.

Core Themes and Conceptual Development We will explore children’s conceptual development in the context of the four overarching themes of this book:

Nature and nurture. Are certain concepts innate (nature)? There is evidence to suggest that certain domains, such as biology, have an innate foundational core evident in infancy and early childhood. Regardless of any innate predisposition, experience and education (nurture) play an instrumental role in elaborating on conceptual knowledge.

Continuity and discontinuity. Our emphasis of nativism and IP theory highlights the continuity– discontinuity theme in this chapter. Both of these theories argue for continuity in conceptual development. However, because children’s conceptual theories undergo revision, this also indicates a discontinuity view.

Domain general and domain specific. The nativism (naive theory) perspective proposes that domain-specific processes operate for particular concepts. On the other hand, the IP approach adopts a domain-general explanation of conceptual development.

Performance and competence. The performance–competence theme reflects the task of assessing children’s performance without overestimating or underestimating their compe- tence (knowledge). Different tasks for measuring conceptual understanding lead to different developmental trajectories of conceptual competence.

5.1 Theories of Concepts Consider two basic concepts: furniture and planes. Take a moment and define these concepts so that someone could identify examples of them.

How did you define furniture? How about planes? Was one concept harder to define than the other? Why do you think there is a difference?

A lexical concept is one that can be labeled by a single word and refers to a discrete entity, whether a living being or nonliving object. Generally speaking, most lexical concepts are rep- resented by features or characteristics; for example, a car is a car because it has four wheels and an engine. Other concepts—such as geometry, justice, and time—are not represented by physical features but by more abstract relational features. There are four primary issues in lexical conceptual development:

1. How are concepts defined? For instance, what makes a bird a bird? Are there features that all birds share? Although this seems like a straightforward question, it turns out to be much more complex.

2. Are all concepts defined in the same way? For instance, are furniture and animals defined in the same way? While obviously they refer to different objects, do they

Section 5.1Theories of Concepts

conceptually differ in some fundamental way because one is animate (living) and the other is inanimate (nonliving)?

3. How do children’s concepts develop? What kinds of concepts do infants possess, and how do they change across childhood and adolescence?

4. Do some concepts have special status in terms of innateness? For example, it may be easier for children to learn certain concepts, such as the concept of human faces, because they have special evolutionary importance to humans (Gelman & Noles, 2011).

Let us begin with the first question regarding defining concepts. There are three primary perspectives on lexical conceptual representation that differ in how they describe the rela- tionship between concepts and their corresponding features. These are the classical view; the prototype or probabilistic view (associated with both constructivist and IP theory); and the theory view (associated with nativism, including core knowledge and naive theory), which is described later in this section. The extent to which each of these perspectives is relevant depends on the concept type. In this chapter, we will review a number of concepts that are structured and defined in different ways.

Classical View of Concepts All children must learn their shapes, such as squares, circles, and triangles. Shapes are an inte- gral component of a child’s early mathematical education. Beginning in preschool, teachers spend time teaching children the basic shapes. As their education progresses, children are taught more complex concepts of geometry. Take the very simple concept of a square. Although 3-year-olds may initially learn to recognize a square by its overall appearance, in order to iden- tify or classify new squares, they must abstract a square’s critical features even if they cannot explicitly express what those features are. The features of a square are well defined. A square is an enclosed figure with four sides of equal length. Is this true of all squares? Are there any squares without these features? The answer to the first question is yes, and the second is no. In other words, squares are defined by a set of necessary and sufficient features.

This viewpoint is referred to as the classical view of concepts (see Medin & Smith, 1984). This perspective has a long history in Western thought (Spalding & Gagné, 2013). It was once argued that all concepts are defined the same way by a set of necessary and sufficient features. Indeed, concepts such as square, odd number, and water can be described in this manner. Much of children’s mathematical knowledge and some scientific knowledge involves learning concepts that are classically defined.

The difficulty with the classical view is that not all, or even most, concepts are defined this way. Consider the concept of a chair. Are there fea- tures common to all chairs? Do all chairs have a seat and back? Most likely many do, but a bean- bag chair does not have a back in the same way as other chairs.

Serezniy/iStock/Thinkstock Chairs vary in the features they share with other chairs. This problem exposes the limitations of the classical view and has led to alternative views of concepts.

Section 5.1Theories of Concepts

In addition to all chairs not having the same set of features, there are other problems with the classical view. For instance, other types of furniture, such as sofas, also have a seat and back but are not chairs. Perhaps chairs could be defined by their function of being something to sit on. However, many objects can be sat on that are not chairs. Fundamental difficulties of defining the necessary and sufficient features for most concepts has led to the development of different descriptions for how concepts are represented (Rosch, 2002).

Prototype or Probabilistic View of Concepts The probabilistic view overcomes the limitations of the classical view. It is associated with the IP perspective because it focuses on how conceptual information is encoded or repre- sented in memory. According to this view, concepts are represented by prototypes. A proto- type is defined as the best example of a concept as determined by rankings from members of a culture. What bird is the best example of the concept bird? If provided a list of birds, most individuals in the United States might rank an eagle or a blue jay as most typical of birds. An ostrich would be listed as less typical of birds, although it is still a bird nonetheless. It shares some features with eagles and blue jays. The degree of perceptual similarity between differ- ent instances of a concept is family resemblance. Eagles and blue jays have a higher family resemblance than ostriches and blue jays. Thus, according to this probabilistic view, different examples of a concept do not always share the same features. This perspective differs from the classical view that argues that lexical concepts have the same set of necessary and suf- ficient features (Murphy, 2002; Spalding & Gagné, 2013).

The probabilistic view also emphasizes the organization of concepts into hierarchical levels. As shown in Figure 5.1, the concept of furniture has different levels of specificity and inclusiveness. At the top of the hierarchy is the superordinate level, which is the most general. In this example, animal and furniture are superordinate concepts. Below the superordinate level is the basic level. Concepts at this level are more similar than super- ordinate concepts because they share many features. In the current examples, the basic level includes different types of furniture, such as chairs and beds, and different types of animals, such as dogs and fish. Adults and children prefer to use basic-level terms in most contexts, such as when labeling an object (Graham, Cameron, & Welder, 2005; see also Gel- man & Davidson, 2013).

The subordinate level is the most specific level of the hierarchy and is below the basic level. At this level, items in a category are highly similar to each other. In our chair example, the subordinate level includes various types of chairs: high chairs, kitchen chairs, dining room chairs, and others. Chairs in the “high chair” category, for example, are more similar to each other than to chairs in the other categories.

Section 5.1Theories of Concepts

Figure 5.1: Conceptual hierarchy

The three hierarchical levels for categorizing objects at increasing levels of specificity, from the superordinate to the subordinate level.

Animals FurnitureSuperordinate

cats tablesdogs chairshorse bedsBasic

beagle kitchencollie diningSubordinate

These differences in similarity across the hierarchical levels have implications for teach- ing children new vocabulary and conceptual information (Gelman & Davidson, 2013). For instance, if a third-grade science teacher was starting a new unit on mammals, should he or she begin by teaching about mammals at the superordinate level or at one of the lower levels? The relevance to education will be considered in more depth later in the chapter.

One of the problems with the probabilistic view is that it treats all features as equivalent in representing a concept. In reality, however, some features are more critical to membership than others. For example, for the concept of car, the feature has four wheels is more necessary than the feature has four doors, because all cars have four wheels, whereas only some cars have four doors. This distinction has led to the development of a theory view of concepts. According to this view, concepts not only need to represent the features, but need explanatory principles to identify which features are important to the concept as well as other informa- tion relevant to classification (Gelman, 2006).

Theory View of Concepts The theory view of concepts incorporates explanatory principles regarding the ontology (ori- gins), causal principles, functions, and intentions of particular concepts, such as living things. Most of these principles are not directly observable (Gelman & Koenig, 2003). The internal mechanisms by which animals move or plants grow, for example, are not observable, yet they are recognized as inherent aspects of these concepts. The theory view of concepts argues that children make certain assumptions about different conceptual domains. According to this view, which is associated with the nativist perspective, children’s knowledge of cognitive domains can be represented by naive theories, which undergo revision with development much as scientific theories undergo revision (Gelman & Noles, 2011).

Children have naive theories about core domains: folk biology, folk physics, folk psychology (also known as theory of mind, which is described in Chapter 6), and geometry. Naive theo- ries have three components (Gelman & Noles, 2011):

• Ontological: The types of entities that a theory explains. For example, a folk biology theory focuses on living entities, whereas folk physics examines objects and their movement through space.

Section 5.2The Probabilistic View and Perceptual Concepts

• Causal laws: The theory’s explanation of the action of those entities will vary depending on the domain. Biological causation would use airborne processes to explain disease transmission, whereas physical causation would use mechanical forces such as gravity to explain object movement.

• Coherence: The interrelationship of the beliefs or laws reflected in the theory. The principles of mechanical forces, for instance, are linked together so they work in unity.

Later in this chapter, we will cover biological and spatial (geometric) concepts that reflect the naive theory view of core concepts. For instance, even 3-year-olds recognize that living things, or animates, differ from nonliving, or inanimate, objects. They expect living things to grow and move on their own volition, whereas they expect inanimate objects to need some external mechanism for their movement. Similarly, to navigate their environment, children need to understand spatial relationships and basic elements of geometry. Theory views can also be applied to concepts that are not considered core knowledge domains but that require explanatory principles to understand their meaning, such as the concepts of jail and news (Gelman, 2013; Keil, 1989).

In summary, concepts are mental representations of the objects and ideas of the world that provide their mean- ings or definitions. Concepts organize children’s and adults’ environment by grouping discrete objects and other entities into common categories. This enables inferential reasoning to predict the properties an item shares with other members from the same category. Much of education consists of teaching children a vari- ety of concepts, from physical objects to more abstract concepts. The next sections describe the development of different concepts.

5.2 The Probabilistic View and Perceptual Concepts As 7-month-old Jessica was driven home from a trip with her father, she gazed out the win- dow at the changing scenery. Her dad wondered what she was looking at and what she under- stood about what she saw. Did she recognize that the dog running in the park was similar to the family’s dog? William James, one of the founders of psychology, described the infants’ world as one of a blooming, buzzing confusion—suggesting that infants in the first few weeks or months are inundated with sensory input that they are initially unable to make meaning- ful. Although this view is no longer accepted (see Chapter 2), infants need to develop concepts to organize their world.

In this section, we explore the development of perceptual concepts across childhood. The majority of research on concepts has focused on either the probabilistic view or the theory view. Perceptual concepts are based on physical appearance rather than a deeper level of understanding. For instance, children’s initial concepts of dogs and trucks are likely based on perception or appearance, rather than on a fundamental level of whether they are living and nonliving things. For this reason they are examined through the lens of the probabilistic view, which focuses on features and appearances.

Questions to Consider

1. Consider the following three concepts: odd number, boat, and gold. Which of the three views of conceptual represen- tation is most applicable to each con- cept? Explain why.

2. What difficulties did you encounter with this exercise?

Section 5.2The Probabilistic View and Perceptual Concepts

Infant Perceptual Concepts Infants’ understanding of their physical world is surprisingly sophisticated, as described in Chapter 2. They understand that objects move through space and persist over time. Of inter- est in this section is whether infants can form perceptual concepts based on their ability to categorize objects (Maurer, 2014; Quinn, 2011). Whether infants have naive theories about particular concepts will be addressed in a later section.

Infants and Basic-Level Concepts Many studies have investigated the perceptual basis of infant concepts. According to the probabilistic view, basic-level concepts are the preferred way of categorizing objects for both children and adults (McDonough, 2002). From this initial classification, we then form super- ordinate and subordinate categories. Does this developmental progression apply to infants as well?

To investigate infant perceptual concepts, a habituation–dishabituation procedure is fre- quently used. As shown, one study familiarized (that is, habituated) 3- and 4-month-old infants to photographs of a variety of cats. After familiarization, infants were shown novel cats and novel examples of other basic-level animal categories, such as birds, horses, dogs, and tigers. To show that they had formed a basic-level category for cat, infants needed to gen- eralize familiarization to the novel cats. They should continue to habituate to the novel cats because they recognized them as additional cat examples. Essentially, they “think,” “Oh I’ve seen those before—more cats.”

How should infants react to novel examples of catego- ries of birds? If their concept of cats does not include birds, they should prefer to look at these different cat- egory members because they are novel and perceptu- ally different from cats. This is exactly how the young infants responded, indicating basic-level categorization by 3 months (Quinn, Eimas, & Rosenkrantz, 1993; Quinn, 2004; Quinn, 2011).

Infants and Superordinate Concepts Infants’ ability to categorize at the superordinate level has been explored as well. Superordinate cat- egories have also been referred to as global catego- ries. To examine superordinate categorization in 3- to 4-month-olds, infants were familiarized to dif- ferent mammals. These included dogs, cats, tigers, rab- bits, zebras, and elephants. This was followed by new mammals (deer) and nonmammals (birds, fish, and furniture). Infants generalized to other mammals and showed a novel preference for all the nonmammals (Behl-Chadha, 1996). To habituate to all the mammals indicates that the infants identified some common properties they all shared.

GlobalIP/iStock/Thinkstock Infants were shown a series of cat pictures and then presented with pictures of other animals, such as dogs, to test whether they could form basic-level categories. Three- and 4-month-olds were able to form basic-level categories because they spent more time looking at pictures of novel animals.

Section 5.2The Probabilistic View and Perceptual Concepts

These results suggest that by age 3 months, infants can categorize at both the basic-level and superordinate-level categories. The basis of both category types is likely the perceptual simi- larity between category members based on family resemblance.

Such patterns raise the issue of how these category levels develop. Do basic-level categories emerge from superordinate categories, or do superordinate categories emerge from basic level? A study of 2-month-olds indicated that infants more easily formed superordinate cat- egories rather than basic-level categories (Quinn & Johnson, 2000). These seem to indicate that global or superordinate categories are more discriminable than basic-level ones. In other words, there are more differences between superordinate concepts (such as furniture and mammals) than between different basic-level categories (such as dogs and cats). Although basic-level categories are typically thought to emerge prior to superordinate ones among children age 3 years and older, these results suggest that a different pattern may be present in infancy (Mervis & Crisafi, 1988).

Infants and Subordinate Concepts To this point, we have considered the establishment of superordinate and basic-level catego- ries. Developing subordinate-level categories requires infants to recognize the similarities between different Siamese cats, for instance, and to distinguish them from other cats, such as tabby cats. According to the probabilistic view, this is difficult because although the similarity among different Siamese cats is high, the similarity between Siamese and tabby cats is rather high as well. Thus, it is challenging to distinguish between the two breeds of cats (Rosch, Mer- vis, Gray, Johnson, & Boyes-Braem, 2004).

There are developmental changes in the establishment of subordinate categories. At age 3 to 4 months, infants were unable to form a subordinate category for Siamese cats or for beagle dogs. Older infants age 6 to 7 months could form some subordinate categories, but not others (Quinn, 2004). The ability to categorize at the subordinate level for some concepts but not others may be attributable to differences in prior exposure to the stimuli, including cultural differences (Quinn & Tanaka, 2007). Further, the perceptual similarity or dissimilarity among all the items may affect whether categories can be formed (Mather & Plunkett, 2011). Putting the results from these studies together, it appears that infants’ perceptual categories become progressively differentiated. Their initial categories are at the global or superordinate level, followed by the basic level, and then the subordinate level.

Behavioral and Brain Measures of Infants’ Perceptual Categories Investigating very young infants’ perceptual categories requires using visual looking time as the measure. Infants’ ability to form categories at 8 months and older has been tested using behavioral measures, such as the sequential touching procedure first described in Chapter 2. In these studies, infants and toddlers are given toys from various categories and asked to “play with them” or “fix them up.” Varying the toys from different categories allows research- ers to examine infants’ and toddlers’ ability to distinguish basic-level and superordinate cat- egories (Mandler, 2007; Mandler, Bauer, & McDonough, 1991).

In one such study, a series of experiments with infants and toddlers from 12 to 20 months old, researchers demonstrated that the children could form both basic-level and global-level categories. If given a set of toy dogs and cats, children tended to put together members from

Section 5.2The Probabilistic View and Perceptual Concepts

one category in a sequential manner. They would touch the different dog exemplars and then touch the different cat exemplars (Mandler & Bauer, 1988).

However, they were also able to differentiate global or superordinate categories. Subsequent studies have varied the category contrasted, such as dogs and fish (basic-level distinctions), against animals and vehicles (superordinate-level distinctions). Because dogs and fish are perceptually more similar than animals and vehicles, it should be easier to distinguish the animals from the vehicles than the dogs from the fish. This is exactly what researchers found. Developmentally, by 18 months children can reliably form global categories. It is not until age 2.5 to 3 years that they can reliably form basic-level categories using this procedure (Mandler et al., 1991).

Thus, whether measured using looking time or sequential touching, children’s acquisition of different perceptual categories progresses from global to basic to subordinate. Note, however, that the ages of this progression varied depending on the measure used. This relates to the performance and competence distinction introduced in Chapter 1. Different measures tap into different levels of understanding. Whereas infants less than 1 year old can demonstrate an implicit understanding of category structure, older infants and toddlers have developed more explicit representations of that knowledge.

In addition to looking time and behavioral measures, researchers have also employed brain evoked-response potential (ERP) measures to identify brain regions associated with the cat- egorization of concepts (Quinn, Westerlund, & Nelson, 2006). ERPs assess what brain regions are activated when a specific stimuli is presented. In a study of 6- to 7-month-olds, neural activity in responses was mea- sured as different levels of categories were being formed. Categorizing items at the subordinate level elic- ited different neural responses than what was found for basic-level items, indicating different processes are involved (Quinn, Doran, Reiss, & Hoffman, 2010).

Perceptual Concepts in Childhood The pattern of conceptual development in infancy is different than that seen in childhood, as previously noted. The basic level is the preferred level of naming objects in both adults and children (Rosch et al., 2004). Typically, children’s first words are basic-level words. Adults also tend to use basic terms over superordinate and subordinate categories when they talk to children (Singer-Freeman & Bauer, 1997). If a father points out a bird to his daughter, he is most likely to say “look at the bird” rather than “look at the animal.” Children also will typi- cally name an animal with, for example, the word dog, rather than animal or collie. If asked to identify an object as a category member, reaction times are faster for basic-level categories than superordinate or subordinate categories. For instance, children and adults are quicker to answer the question “Is a robin a bird?” than “Is a bird an animal?” (Jerger & Damian, 2005).

According to the probabilistic view, the basic level is preferred in childhood because category members at this level are most easily understood in terms of the features they share or do not share (Rosch et al., 2004). The concept of cat is distinctive from other basic-level concepts such as bird, because cats and birds do not share many features. However, different exemplars

Question to Consider

What would be the implications for understanding infant cognition if infants were not able to form perceptual concepts?

Section 5.2The Probabilistic View and Perceptual Concepts

of birds share many features; for example, robins, blue jays, and crows are highly similar, allowing children to have a sense of what makes a bird a bird (Rosch & Mervis, 1998).

Concepts at both the superordinate and subordinate levels are more difficult to learn, although for different reasons. Let us imagine that a kindergarten teacher is teaching children the names of different breeds of dogs. Consider the case of the collie concept. All collies gener- ally look similar; the difficulty is that some other breeds also appear similar to collies, such as golden retrievers. Identifying the specific features that distinguish collies from retrievers can be subtle.

Superordinate-level terms also present learning challenges, although for opposite reasons. Again, imagine that 5-year-olds are being taught superordinate terms such as vehicles and furniture. Vehicles and furniture do not share much perceptual similarity, so they should be easy to distinguish. However, within the furniture category, members such as table, bed, and chair do not share much similarity either. Consequently, children would have more difficulty identifying the basis of categorization (Liu, Golinkoff, & Sak, 2001).

Class Inclusion An important aspect of the probabilistic view of conceptual knowledge is the hierarchical rela- tionship between different levels of concepts, as illustrated previously in Figure 5.1. Children must learn that these hierarchical relationships involve inclusive relationships, sometimes referred to as class inclusion. Class inclusion is the understanding that a particular category is a subset of a larger category. For instance, the superordinate category of animals includes all basic-level animals of dogs, fish, and others. The basic-level category of dog includes all subordinate-level dogs, such as collies, beagles, and others.

Piaget was one of the first to describe children’s difficulty with class inclusion during the preoperational stage (Inhelder & Piaget, 1964). The class-inclusion task is illustrated in Figure 5.2.

Figure 5.2: Piagetian class-inclusion task

The class-inclusion task assesses children’s understanding of the inclusive nature of the conceptual hierarchy.

Section 5.3Theory View and Biological Concepts

Preoperational children make mistakes in the class-inclusion task because of the logical limi- tation of preoperational thought. As described in Chapter 1, they demonstrate centration, which causes them to be misled by appearances, and cannot consider multiple relationships at the same time (Inhelder & Piaget, 1964). In this class-inclusion picture, since there are more dogs than cats, preoperational children respond “more dogs” when asked whether there are more dogs or more animals. They fail to understand that a lower level category is included within a higher order (Inhelder & Piaget, 1964). It is not until age 9 that children fully master class inclusion (Deneault & Ricard, 2005). This is similar to their difficulty in the conservation task described in Chapter 1. In the conservation task, preschoolers do not simultaneously consider both the height and width of the beakers.

In summary, children can form perceptual concepts beginning in infancy. Depending on the assessment pro- cedure, infants and children vary in their development of different levels of the hierarchy. Infants progress from the global to the basic to the subordinate levels. In contrast, beginning around age 2 or 3, children prog- ress from the basic to the superordinate to subordinate levels. Understanding the inclusive nature of a concep- tual hierarchy develops later.

5.3 Theory View and Biological Concepts We have thus far covered perceptually defined concepts. Three-year-olds, and even infants, can perceptually distinguish between concepts such as dogs and cats and recognize that dif- ferent dogs belong to the same category. However, conceptual understanding is deeper than this. Identifying perceptual concepts does not answer the question of what children under- stand about these categories beyond their physical appearance. We will illustrate the devel- opment of a more complex conceptual understanding using the domain of biology, which is a core domain.

For most conceptual domains, children have misunderstandings or misconceptions, even if they have a naive theory about that domain. Biology is no exception. In this chapter’s case study, Yao and her classmates already knew something about bugs, but their knowledge was incomplete. For instance, 3- to 5-year-olds struggle with what it means to be “alive” and have trouble believing that plants are alive (Leddon, Waxman, & Medin, 2008; Nguyen & Gelman, 2002). In many ways formal education consists of overcoming children’s misconceptions to create conceptual change. Because it examines principles beyond the immediately percep- tible, the theory view of concepts will be the focus of most of this section.

Take a moment to think about how you would characterize the differences between living things and inanimate objects. How many differences can you come up with?

You probably mentioned that animates have self-generated motion; they grow; and they have distinctive perceptual characteristics (such as eyes and a nose) among other differences. If children have some similar understanding of the animate and inanimate distinction, then this might imply they have conceptual knowledge about biological and nonbiological concepts (Opfer & Gelman, 2011).

Question to Consider

Because perceptual concepts are formed based on appearance, what type of information is missing? For instance, what else do children need to know about cats to form a deeper understanding of cats?

Section 5.3Theory View and Biological Concepts

This animate–inanimate distinction is part of a broader conceptual distinction between natu- ral kinds and artifacts. Natural kinds are found in nature and include animates, plants, and minerals. Artifacts are objects designed by humans and include tools, furniture, and the like. Table 5.1 lists some of the primary characteristics that distinguish between natural kinds and artifacts (see Gelman, 2013; Keil, 1989).

Table 5.1: Properties of natural kinds and artifacts

Natural kinds Artifacts

Shared chromosomal or molecular structure Shared intended function

Insides are important to identity Insides are less important to identity

Changes in appearance do not change identity Changes in function change identity

Has a natural origin Is manufactured by humans

Source: Gelman, 1988.

It should be noted that this distinction may be culturally specific. The differences identified in the table reflect Western culture’s general acceptance of scientific knowledge to ultimately decide the identity of a natural kind. Other cultures may use other criteria (Atran & Medin, 2008; Liu & Unsworth, 2014; Lucy, 2011). Of interest has been whether children appreciate this distinction and reason differently about natural kinds and artifacts.

If children do reason differently about natural kinds than artifacts, this raises the issue of the origins of this knowledge. As with infants’ physical knowledge described in Chapter 2, the debate is whether understanding natural kinds, including biological concepts, reflects a core knowledge domain (sometimes represented as a naive theory) or whether it is acquired through experience. According to the nativist perspective, humans have evolved predisposi- tions to attend to biological entities in general, especially to humans, although these predis- positions can be modified. In the following section, the nativist perspective will be compared to more experience-based perspectives for both biological and spatial concepts.

Biological Concepts in Infancy If children have a predisposition to attend to biological entities, then this preference might be exhibited in infancy. Faces represent one type of biological concept because they are characteristic of living things. Considerable research has examined whether newborns and young infants exhibit a face bias (Farroni et al., 2005; Wilkinson, Paikan, Gredebäck, Rea, & Metta, 2014).

In a classic illustration of this attentional bias toward faces, newborn infants were shown the stimuli depicted in Figure 5.3 (Johnson, Dziurawiec, Ellis, & Morton, 1991). Researchers mea- sured infants’ eye tracking (where they looked) to see if they prefer looking at faces.

Section 5.3Theory View and Biological Concepts

Figure 5.3: Do infants have a preference for faces?

Infants were exposed to these different stimuli to examine whether they prefer to look at a human face over equally complex stimuli.

Using eye-tracking, it was measured that infants preferred looking at human face displays. At one month, this preference decreases and comes back at three months.

Face Con�g Inverse Linear

Source: Adapted from Johnson, M. H., Dziurawiec, S., Ellis, H., & Morton, J. (1991). Newborns’ preferential tracking of face-like stimuli and its subsequent decline. Cognition, 40(1–2), 1–19. doi: 10.1016/0010-0277(91)90045-6. Reprinted with permission from Elsevier.

This increased attention to faces is also exhibited by examining eye tracking of realistic faces in either an upright configuration or inverted configuration. Infants aged 4.5 to 6.5 months preferred to scan the eyes of upright faces but changed to scanning more of the face, includ- ing the mouth, by around 6 months, the age when infants begin to focus on learning language. There was no such change in their scanning of inverted faces, indicating they did not catego- rize them as a face (Oakes & Ellis, 2013; Rose, Jankowski, & Feldman, 2008). ERP measures also show that 6- and 7-month-olds have different neural responses to upright faces and inverted faces (Balas et al., 2010).

Experience is necessary for the subsequent development of face perception. For instance, early in development, 5-month-old infants can discriminate between both human faces and monkey faces. Over time they maintain the ability to discriminate between human faces but lose the ability to distinguish the faces of monkeys (Pascalis, de Haan, & Nelson, 2002; Scott & Fava, 2013). These developmental changes suggest that face preference is modified as infants get more experience with human faces.

In line with this perspective, infants develop preferences for faces from their own racial groups over the first year of life (Anzures, Quinn, Pascalis, Slater, & Lee, 2013). Infants also show preferences for female faces over male faces by age 3 months (Quinn, Yahr, Kuhn, Slater, & Pascalis, 2002; Quinn et al., 2008), indicating that experience fine-tunes this preference (Frank, Amso, & Johnson, 2014).

In addition to faces, infants show an early ability to detect biological motion over nonbiologi- cal motion. In these experiments, children are shown dynamic point-light displays. The dis- plays represent someone walking and can be manipulated to mimic different types of walking.

Section 5.3Theory View and Biological Concepts

Infants as young as 2 days old can discriminate between point-light displays of walking and a random configuration of moving dots of the same complexity. Perhaps more critical to deter- mining if this detection of biological motion reflects an evolutionary adaptation is the finding that infants show a preference for looking at biological motion over nonbiological motion (Simion, Regolin, & Bulf, 2008). Infants can distinguish between objects that move in an intentional or goal-oriented manner from those that move in a random manner (Luo, 2011).

Spotlight on Research: Detection of Biological Motion http://www.biomotionlab.ca/Demos/BMLwalker.html

Children and adults can detect biological motion based on dot patterns of light moving in a walking configuration. You can manipulate the characteristics of the walker. Give it a try! Con- sider how you could use this tool to assess cognitive development in infants.

Together, the evidence from infancy suggests that infants have a predisposition to attend to and prefer faces and biological, intentional motion. This supports the nativist perspective that biology may represent an innate specialized domain in line with the core knowledge view. However, keep in mind that children still need experience to fine-tune these initial pre- dispositions. The interaction between predispositions and experience reflect the nature and nurture theme of Chapter 1. Development almost always consists of an interaction between nature and nurture (Moore, 2013a). Face processing continues to develop through adoles- cence and into young adulthood based on experience with different types of faces (Scherf & Scott, 2012).

Biological Concepts in Childhood This section discusses children’s biological understanding at a conceptual level, rather than a perceptual level. Understanding children’s preferences and biases, as well as their conceptual understanding, is directly relevant to education and intervention for typically and atypically developing children.

Consider the following story, which was told to children in a study:

The doctors took a raccoon (show picture of a raccoon) and shaved away some of its fur. They dyed what was left all black. Then they bleached a single stripe all white down the center of its back. Then with surgery (explained to child in preamble) they put in its body a … sac of super smelly yucky stuff. When they were all done the animal looked like this (show picture of skunk). After the operation was this a skunk or raccoon? (Keil, 1989, p. 184)

How might you answer the same question posed to children about the animal’s identity? How would you explain to a child what the animal is after the operation?

For educators, understanding that children may have biases toward certain types of concepts can help design lessons to provide a deeper understanding of these concepts. Concepts that may not have the same predispositions—such as historical concepts—may require different

Section 5.3Theory View and Biological Concepts

types of instructional lessons. Beginning during the preschool years around age 3, children’s understanding of biological concepts can be more directly examined. In this section, we con- sider two theoretical perspectives.

One influential view is the naive theory view of cognitive development discussed in Chapter 1. According to this view, children possess naive theories about certain conceptual domains, including biological concepts (Gelman, 2003). We contrast this perspective with a similarity- based view that is closely aligned with the probabilistic view of concepts (Sloutsky, 2003).

Let us return to the raccoon/skunk story. Most likely you argued that changing the rac- coon’s appearance did not change its basic identity. But do children reason the same way? To investigate this, kindergartners, second graders, and fourth graders were told the rac- coon transformation story as well as artifact transformation stories, such as changing a pipe into a flute.

For natural kinds, there was an increase in the age at which children replied that the identity did not change (that is, they said the raccoon was still a raccoon). For artifacts, however, chil- dren of all ages said that the identity of the artifact did change. The pipe had indeed become a flute. The following conversation between the experimenter (E) and a second-grade child (C) illustrates children’s different reasoning about natural kinds and artifacts:

C: Raccoon … just because they made it look like a skunk, it’s not really one.

E: Why is it still a raccoon? It looks just like a skunk.

C: It looks like a skunk and has its smell.

E. But it is still a raccoon?

C: Yes.

E: Why could you change a pipe into a flute, but you couldn’t change a raccoon into a skunk?

C: One’s alive and one’s not. (Keil, 1989, p. 189)

Thus, early in development, children treat natural kinds and artifacts differently, although these differences become enhanced with age. In the prior example, the second graders clearly understood that because the raccoon was living, its identity could not be changed. As an artifact, since the pipe is not living, its identity can be changed to a flute. Artifacts are defined by their function as well as their appearance. Changing the function changes their identity. For example, recycled plastic bottles made into lawn furniture are no longer seen as plastic bottles.

Scientists are confronted with similar issues when a new or unknown species is found. To determine its true identity, they typically refer to its DNA, because our scientific theories specify genes as the ultimate determinant of identify. Although children do not have precise scientific theories, they do have naive theories about specific domains such as biology that are similar to scientific theories (Gopnik & Wellman, 2012).

Section 5.3Theory View and Biological Concepts

In these examples, children aged 3 to 5 years were able to reason about the nonobvious properties of natural kinds. Understanding the differences between natural phenomena and mechanical ones differs from earlier developmental theories. Piaget (1929) described pre- school or preoperational children as showing artificialism in their reasoning: They believe that natural phenomena, as well as mechanical devices, are created by humans. For example, a 4-year-old might say that the sun was created by someone using a match. This suggests that preschoolers do not understand that there can be internal causes of events. As a consequence,

according to Piaget, it is not until age 6 or 7 that chil- dren can reason about nonobvious properties of natu- rally occurring phenomena. However, recent research has indicated that this is not true (Gelman, 2013).

In the classroom, teachers are often presented with children’s misconceptions about various natural phe- nomena, even if they have naive theories about these concepts. As illustrated in the case study, Joshua thought that rocks could grow. Science education consists of presenting children evidence to overcome these misconceptions.

Biological Categories and Inferences One of the crucial functions of categories is that they support inductive inferences. An induc- tive inference is generalizing known facts about a concept to new exemplars of that concept. Knowing, for instance, the category that an animal or stone belongs to allows predictions about its characteristics. If told that a dog has a property such as leucocytes in its blood, a likely inference is that other dogs have this same property. This inference is made even if this property is not perceptually obvious or whether children even know what leucocytes are. In contrast, artifacts are not expected to have the same internal properties. Different tables can be made out of different materials: Some can be made of steel and some of wood (Gelman, 2013).

Children’s patterns of inductive inferences can be examined using a variety of tasks (Gelman & Davidson, 2013). Consider the experiment illustrated in Figure 5.4. As the figure shows, children are taught different novel properties about the bird and bat. The selection of blood is important because it is a nonobvious property that natural kinds would be expected to share.

The same use of category membership for inferences for nonbiological natural kinds, such as gold, was also found. Moreover, children’s inferences were principled. They did not make category-based inferences for all properties, but only for ones that are core to category mem- bership. For instance, returning to the bird and bat example, children were also taught that “this bird’s legs get cold at night” and “this bat’s legs stay warm at night.” It would not be expected that other category members would share this property. For this property, children were at chance level (50%) for using category membership (Gelman & Markman, 1986; Gel- man, 2003).

Questions to Consider

1. How would you teach Joshua that rocks do not grow? For example, would you simply tell him, or would you set up a situation for him to discover it for him- self? Or would you try something else?

2. Why do you believe your method would be the most effective?

Section 5.3Theory View and Biological Concepts

Figure 5.4: Inductive inference task

Though the target bird is perceptually more like the bat than like the flamingo, children in the study understood that the target shares properties with the flamingo because it belongs to the same category.

Source: Adapted from Gelman, S. A., & Markman, E. M. (1986). Categories and induction in young children. Cognition, 23(3), 183– 209. doi: 10.1016/0010-0277(86)90034-X.

Psychological Essentialism Do children reason about natural kinds, particularly biological concepts, and artifacts dif- ferently? In a study of inductive inferences involving both natural kinds and artifacts, 4- and 5-year-olds did not make clear distinctions between natural kinds and artifacts. However, by second grade, children made more category inferences for natural kinds than for artifacts (Gelman & Markman, 1987; see also Neary, Van de Vondervoort, & Friedman, 2012; Rhodes & Gelman, 2009). As discussed earlier, insides are particularly important to the identity of natural kinds. In studies, children as young as ages 3 and 4 years have demonstrated under- standing that members of the same natural-kind category are more likely to share the same kind of insides (see Gelman, 2003; Gelman & Wellman, 1991).

The finding that children expect natural-kind concepts to share nonobvious properties with which they are not familiar indicates psychological essentialism. Psychological essentialism is the belief by children and adults that categories have an underlying reality or essence that accu- rately divides the natural world at its boundaries. This essence is reflected in children’s naive theories. The specific details of this essence may be unknown (Gelman, 2003; Medin, 1989).

Section 5.3Theory View and Biological Concepts

Thus, natural-kind categories are real categories that share properties even if those are not observable and not known. That is, they have an essence, whereas artifacts do not. Recall the earlier studies of transforming skunks into raccoons and pipes into flutes. Even though the raccoon looked like a skunk, its essence or “skunkiness” had not changed. However, the pipe did not have a similar essence of “pipeness” that was maintained through its transformation into a flute. However, it has been recently proposed that artifacts may also have a type of essence if they have historical or personal significance, such as a famous painting or trea- sured object from childhood (Gelman, 2013).

The Similarity-Induction Perspective on Biological Concepts Some researchers suggest that children’s initial understanding of biological concepts is based on perceptual similarity among category examples and not on the conceptual assumptions proposed by the naive theory view (Fisher & Sloutsky, 2005; Sloutsky, 2010). This similarity- induction perspective is more aligned with the probabilistic view because it emphasizes perceptual cues (similar to family resemblance). There are differences, too: For example, the similarity-based approach provides more emphasis on the transition from perceptual to abstract concepts (Sloutsky, 2010).

To test the role of appearance in category induction, 4- and- 5-year-old children were taught the labels for new (made-up) bugs, as shown in Figure 5.5. The advantage of employing novel categories is that it controls for prior knowledge. The category definitions of ziblets and flurps were based on a rule and not on similar overall appearances. Can you tell the difference? Ziblets were distinguished from flurps by the number of fingers and buttons they had. Ziblets had more fingers than buttons, and flurps had more buttons than fingers. The other features (tail, color, and so on) could occur in either ziblets or flurps. Thus, cat- egory membership was fairly independent of overall perceptual similarity (Sloutsky, Kloos, & Fisher, 2007).

In contrast to the naive theory view of concepts, these results suggest that young children are making inferences based on perceptual similarity. This reliance on perception has been documented in children as old as 7. It is not until around age 11 that children make inferences based on category membership (Fisher & Sloutsky, 2005). This transition from perceptual- based to category-based inferences may come from learning specific categories. Children, in fact, are more likely to make categorical inferences for familiar than unfamiliar biological concepts (Farrar & Boyer-Pennington, 2011).

Section 5.3Theory View and Biological Concepts

Figure 5.5: Novel bugs in an inductive inference task

In this study, children selected the same-appearance item rather than the same-category item 73% of the time. This suggests that they rely on perceptual similarity and not categorical memberships.

Source: Adapted from Sloutsky, V. M., Kloos, H., & Fisher, A. V. (2007). When looks are everything: Appearance similarity versus kind information in early induction. Psychological Science, 18(2), 179–185. doi: 10.1111/j.1467-9280.2007.01869.x.

Experience and Inductive Inferences Whether children use initial biases or perceptual similarity in reasoning about biological con- cepts, they need experience and to be taught to acquire new concepts and to fill in the gaps of their knowledge. Although both naive theory and similarity-based approaches acknowl- edge the role of experience and culture in the development of biological conceptual knowl- edge, there are few direct investigations. To address this, researchers compared four groups of 4-year-olds whose parents were either biological experts or novices and who either lived in an urban or rural environment (Tarlowski, 2006). Parents classified as experts worked as zookeepers, veterinarians, researchers, and other biology-related careers.

Children were administered a projection task, which is similar to an induction task. In a pro- jection task, children are taught a property about a base concept. The base concepts were either human, mammal, or insect. Children had to project (infer) whether each of nine tar- gets also possessed that property. The targets differed in their category similarity to the base concept. Children who lived in rural environments or whose parents were experts made

Section 5.3Theory View and Biological Concepts

fewer projections than the other children. These children were knowledgeable about bio- logical concepts because of their experiences, which enabled them to be selective in their reasoning (Tarlowski, 2006). These results are consistent with the similarity-based argument that children’s biological knowledge derives from experience and the acquisition of scientific knowledge.

Both perceptual similarity and category membership influence children’s inferences. Three- and 4-year-olds also use functions more than similarity to govern their inferences. For instance, understanding that webbed feet can be used for swimming can lead children to infer that other animals with webbed feet also swim (Keleman, Widdowson, Posner, Brown, & Casler, 2003). Thus, children use numerous types of information to guide their inferences.

Biological and Scientific Concepts in the Classroom Regardless of whether children have naive theories or biases, many of the specific details children learn about biological (and other) concepts are acquired through direct teaching in the classroom or home and through observation. However, their beliefs about science are incomplete, and sometimes they have misconceptions. Science education is designed to fill in the details as well as to correct misconceptions.

In a survey, primary-grade science teachers were asked about children’s common misconcep- tions in both biology and physics (Pine, Messer, & St. John, 2001). Regarding biology (natural kinds), first graders often believe:

• animals are four legged and furry (omitting animals that do not have those features), • a plant’s seed contains a baby plant, • physical growth happens on your birthday, • vision occurs because light comes out of the eyes, and • death is a reversible process.

Children also had misconceptions about physics (folk physics), including:

• an object moving in a curved tube will continue to move in a curved manner after exiting,

• large objects always weigh more than small objects, and • the moon is a source of light.

How do these misconceptions affect science education? Some studies have found it is difficult to change children’s and adults’ strongly held beliefs. Others have found misconceptions are actually a good starting point for teaching because they help identify what children know and do not know (Pine et al., 2001).

How effectively these misconceptions can be overcome may depend on the type of instruction used (Wendt & Rockinson-Szapkiw, 2014). A study of middle school students compared the effectiveness of two types of collaborative interactions in overcoming scientific misconcep- tions. Over a 9-week period, students participated in peer-to-peer live interactions or peer- to-peer online interactions. Both groups were given pre- and posttests to measure their sci- entific literacy. During the experiment, the groups were taught different scientific concepts via collaborative activities.

Section 5.3Theory View and Biological Concepts

The live collaborations were more effective than the online ones in overcoming students’ mis- conceptions. Indeed, there were no changes in understanding for the online collaboration group. One reason for the improvement in the live condition is the immediate responsiveness of the other peer and of the teacher. The immediacy of the feedback and responsive collabora- tion helped children overcome their misunderstandings (Wendt & Rockinson-Szapkiw, 2014).

Other educational approaches contribute to children’s learning about biological and other concepts. Pedagogical learning occurs when a teacher or other knowledgeable person intentionally communicates information to learners. Nonpedagogical learning occurs when learners discover information for themselves through observation or inference. For example, if a child observes that his or her dog chases cats, the child may infer that all dogs engage in the same activity (Rhodes, Gelman, & Brickman, 2010).

Much of formal education involves pedagogical learning in which teachers purposively instruct children about important concepts, including scientific concepts. To illustrate a con- cept, teachers can use a pedagogical sampling strategy in which examples are selected that “clearly and unambiguously” (Rhodes et al., 2010, p. 421) represent the concept. It is more effective to use three different dogs (for example, a collie, a German shepherd, and a golden retriever) than, say, three collies to teach children a property about dogs. They are more likely to extend the property to all dogs when a variety of dogs is used, rather than only one dog.

Children pay attention to sample composition in pedagogical learning earlier in development. For nonpedagogical learning, attending to sample composition first appears in 6- to 9-year- olds (Rhodes et al., 2010). To demonstrate whether kindergartners attend to sample compo- sition, they were compared in pedagogical and nonpedagogical learning conditions.

In the pedagogical sampling condition, children were asked to be the teacher and teach another child a fact about an animal. The child had to choose between two samples of animals to teach this new fact. The samples varied in whether they were diverse or nondiverse. Chil- dren were told:

Your job is to teach this child … that dogs have four-chamber hearts. But, you can’t show her all the dogs in the world to teach they have four-chamber hearts, you can show her three dogs. Which three dogs should you show her to teach about dogs? (Rhodes et al., 2010, p. 427)

The diverse sample consisted of three different types of dogs. The nondiverse sample con- sisted of three of the same type of dogs (Rhodes et al., 2010).

In the nonpedagogical condition, children were told to be a scientist and discover a new fact about animals. As in the other condition, they had to choose whether to select a diverse or nondiverse sample to discover the new fact. Of interest was whether children selected dif- ferent samples in the teaching and scientist conditions. Children in the teaching condition were more likely to select the diverse sample (75% of the time) than the nondiverse sample. However, in the scientist condition, children were equally likely to select either sample type.

These results suggest that kindergartners appreciate the importance of sampling in teach- ing contexts. Prior studies with children from age 6 to 9 years demonstrated similar effects (Rhodes et al., 2010). Children’s distinction between pedagogical and nonpedagogical

Section 5.4Neuroscience and Biological Concepts

samplings in different contexts indicates that they know teachers are intentionally teaching them about a new concept (Rhodes et al., 2010; see also Csibra & Gergely, 2006).

More broadly, the results of the experience and teaching studies indicate that the details of biological knowledge have to be learned. As Vygotsky argued, much of this learning is socially transmitted through interaction with more knowledgeable others. Teachers can create many interactive activities to teach children about different concepts.

Real-World Application: Hey Science Teachers—Make It Fun https://youtu.be/6OaIdwUdSxE

As you view this TED Talk, take note of strategies the teacher used to engage his 13-year-old students in learning science. How would you adapt his approach to younger children?

5.4 Neuroscience and Biological Concepts Most of the evidence we have reviewed suggests that biological concepts represent a spe- cialized domain of knowledge, and experience plays a role in its elaboration and develop- ment. Evidence from neuroscience also supports the idea that certain elements of biological concepts may have a privileged status. Studies with adults have identified particular regions in the right hemisphere that are associated with face processing (Johnson, 2011). As we dis- cussed earlier, studies using ERPs have found that infants have different responses to upright versus inverted faces (de Haan, Johnson, & Halit, 2003), which indicates the existence of spe- cialized neural mechanisms devoted to face processing.

Children’s ERP responses to upright and inverted faces change over the course of their devel- opment. Children who are 3 to 6 months old do not exhibit the pattern that adults display to faces. However, 12-month-olds have a similar reaction as adults, although some changes con- tinue to occur up until middle childhood (de Haan, Pascalis, & Johnson, 2002; Johnson, 2011).

Difficulties in face recognition can occur for typically developing children and adults (Dal- rymple, Corrow, Yonas, & Duchaine, 2012). In severe cases individuals may suffer from “face blindness” or prosopagnosia and be unable to recognize the faces of family members or famous individuals. This selective deficit is evident in specialized brain regions devoted to facial processing and may have a genetic basis (Grütter, Grütter & Carbon, 2008).

Functional magnetic resonance imaging studies can detect activity in different cortical areas of the brain by measuring blood flow. Different types of visual stimuli activate different brain areas. A study involving 8-year-old children, 11- to 14-year-old adolescents, and adults mea- sured brain activity when subjects were presented with faces, objects, places, and buildings. Figure 5.6 illustrates these patterns of brain activity (Scherf, Behrmann, Humphreys, & Luna, 2007). The activation of distinct brain regions for different concepts suggests that the under- lying neural and cognitive processes for concepts can vary depending on the type of concept.

Section 5.4Neuroscience and Biological Concepts

Figure 5.6: Brain activity in response to different concepts

Children, adolescents, and adults showed different patterns of neural activity when exposed to concepts of faces, buildings and navigation, and objects. Somewhat surprisingly, the children showed similar activation patterns to the adults for objects and places but different activation patterns for faces. These facial brain areas did not become similar to adults’ until adolescence.

Source: Scherf, K., Behrmann, M., Humphreys, K., & Luna, B. (2007). Visual category-selectivity for faces, places and objects emerges along different developmental trajectories. Developmental Science, 10(4), F15–F30. doi: 10.1111/j.1467-7687.2007.00595.x. Reprinted with permission from John Wiley & Sons.

Real-World Application: Autism Spectrum Disorders and Biological Knowledge Children with certain developmental disorders, including autism, demonstrate that some aspects of biological knowledge may have a neural basis. Children with autism often demon- strate repetitive behaviors, restricted interests, and deficits in social–communicative behav- iors (American Psychiatric Association, 2013). In particular, children with autism often have selective difficulty with theory of mind concepts (described in Chapter 6), such as false belief (Hale & Tager-Flusberg, 2005). They may also have selective deficits in related aspects of social cognition involving social interactions.

(continued)

Section 5.3Neuroscience and Biological Concepts

Real-World Application: Autism Spectrum Disorders and Biological Knowledge (continued) Children with autism or autism spectrum disorders (ASD) often seem to be less interested in people and spend less time interacting with them than do typically developing children. They look less at faces and tend to avoid eye contact (Klin, Jones, Schultz, Volkmar, & Cohen, 2002). When viewing faces, patterns of brain activity for adults with autism differ from the pattern observed in individuals without autism. This difference is not seen when they view objects (Dalton et al., 2005).

Children with autism also show similar difficulties with face perception and recognition. In one study, the ability of 2-year-olds with ASD to recognize human and monkey faces previ- ously presented was compared to children who were typically developing and to children with developmental delays. In each trial with human faces, children were shown a photo of one face, followed by a pair of photos—one the same face they just saw and one a new face—to determine whether they recognized that one face was familiar. A similar procedure occurred in each trial with the monkey faces. Researchers found that children who were typically devel- oping were better able to recognize human than monkey faces. The children with ASD and the children with developmental delays were unable to recognize any of the faces regardless of the species (Chawarska & Volkmar, 2007). More sensitive measures of reactions to faces have identified differences in face processing in children with ASD, who particularly avoid looking at eyes compared to other facial features (Jones & Klin, 2013).

Children are not typically diagnosed with ASD until they are at least 2 to 3 years old. Research has been focused on identifying early predictors of an ASD diagnosis. One recent study exam- ined whether eye fixation while scanning faces in infancy predicted later ASD diagnosis. In a study, 110 infants, some of whom were more likely to be diagnosed with ASD because a sibling had ASD, were compared with other infants who had no risk factors for ASD. The eye tracking of 2- to 6-month-olds was measured while watching caregiving interactions between parents and children. At-risk infants and those who had a later diagnosis of ASD spent less time fixat- ing on the eyes, while other at-risk children who were not later diagnosed, as well as no-risk children, did not show this pattern of avoiding the eyes (Jones & Klin, 2013).

Thus, there is solid evidence for a neurological basis of face perception that becomes increas- ingly specialized with experience. As we have seen, even if children have built-in or innate predispositions to attend to stimuli such as faces, these predispositions are modified by expe- rience with various types of faces. This is consistent with the nature and nurture interactional perspective on development (Scherf et al., 2007).

Critical-Thinking Question

How might this research about children’s facial processing be translated into teaching prac- tice? In particular, how might a teacher work with a child who prefers to avoid eye contact?

Section 5.5Spatial and Geometric Concepts in Childhood

5.5 Spatial and Geometric Concepts in Childhood Geometric knowledge lays the foundation for formal instruction in geometry and mathemat- ics in schools. Children who have better spatial skills and advanced spatial concepts are more successful in a variety of STEM (science, technology, engineering, and mathematics) courses and occupations (Liben, 2009). As with other concepts discussed in the chapter, there is some evidence for an early basis for spatial and geometric concepts. For example, recall that Chap- ter 2 described infants’ understanding of concepts of space, such as their use of egocentric or allocentric frames of reference to locate themselves and objects in space. However, these kinds of concepts differ in some ways from others discussed in the chapter.

Concepts considered thus far have been discrete physical objects, such as animals, faces, and cars. These concepts have physical features that the three perspectives use to describe their representation, though to differing degrees. Although some geometric concepts such as trian- gles and squares can be defined by their features, many are instead defined by their relation- ships to other locations or objects, such as the correspondence of a map and the environment it reflects. Some of this research is viewed from a core knowledge perspective, similar to the theory view of conceptual development. However, as with biology, children need education and experience to elaborate on geometric concepts.

One aspect of children’s emerging spatial and geometric conceptual knowledge is the use of maps. Using maps to represent a spatial environment is a higher level cognitive skill. To suc- cessfully read a map, children must understand that maps are representations of spatial rela- tionships. Further, they must grasp that the symbols on the map represent different elements in the environment, such as buildings, roads, and other landmarks (Liben, 2009).

These achievements develop throughout childhood and adolescence as spatial cognition develops. Piaget did some of the initial work on children’s spatial thinking (Piaget & Inhelder, 1948/1967) and identified three types of spatial concepts, listed in Table 5.2.

Table 5.2: Spatial concepts

Spatial concept Definition Stage and age

Topological space The transformation of objects through twisting and squeez- ing. The spatial configuration of objects in terms of proximity, separation, order, and enclosure.

Sensorimotor stage (0 to 2)

Projective space The relative position of differ- ent objects in relation to a single observer and not the actual distances.

Preoperational stage (2 to about 6 or 7)

Euclidean space Marking the positions of objects relative to an external frame of reference using vertical and horizontal reference lines.

Preoperational stage (2 to about 6 or 7) and concrete-operational stage (about 6 or 7 to 11 or 12)

Section 5.5Spatial and Geometric Concepts in Childhood

Research has supported some aspects of Piaget’s description of the developmental sequence of spatial cognition, although it has been subject to criticism and revision as well (see Owens & Outhred, 2006, for a review).

Let us begin with Piaget’s classic illustration of children’s difficulty in understanding Euclid- ean space (Piaget & Inhelder, 1948/1967). The water-level task, as depicted in Figure 5.7, requires children to draw the correct orientation of the water level in the bottle as it is rotated. As it is turned, the water level is covered, although the top of the bottle is visible. To perform correctly, the child must use an external frame of reference and always draw the water level parallel to the ground regardless of the bottle’s orientation. As illustrated in the performances of 2½-year-old Peter and 4-year-old Jane, this is difficult. Both are unable to use an external frame of reference, but rather draw it relative to the bottle. Children cannot perform this task correctly until about age 9 to 10 (Davis, 1971–1972). However, recent studies have shown that even adults can sometimes struggle with the task, suggesting that some geometric con- cepts emerge over a long time (Liben, 2014).

Figure 5.7: Piagetian water-level task

This classic Piagetian task requires children to understand Euclidean space, particularly the use of horizontal and vertical reference lines.

Source: Adapted from Davis, R. (1971–1972). The structure of mathematics and the structure of cognitive development. Journal of Children’s Mathematical Behavior, 71–97. Cited in Gallagher, J. M., & Reid, D. K. (1981). The Learning Theory of Piaget and Inhelder. Monterey, CA: Brooks/Cole.

Section 5.5Spatial and Geometric Concepts in Childhood

Learning to Use Maps Children’s ability to use maps to find objects or locations in the environment requires an understanding of projective space, which can occur starting around age 3 years but is lim- ited. They still have some difficulties comprehending the relationship between maps and the real world. One difficulty is in iconicity, in which children believe there is perceptual similar- ity between the map and the environment. For instance, if the map represents roads by blue lines, then 3- and 4-year-old children may think the real roads are blue (Liben, 1997).

Maps and their referents have different levels of correspondence. In representational cor- respondences there is a commonly understood symbolic connection between the real-world referents and their symbols on the map. An example is red crosses representing hospitals. Geometric correspondences reflect spatial links between the location of the symbol on the map and the referent’s location in the real world. For example, if the map indicates a school above a river, then in the real environment the school is north of the river. Both features are needed to create and understand a map. Under simplified testing conditions, children are able to use representational correspondence without employing geometric correspondence to identify the locations of objects in an environment from a map (Liben, 2009; Liben, Myers, Christensen, & Bower, 2013).

By age 6 years, children from a variety of cultural backgrounds can typically use geometric maps based on spatial relationships of distance, lines, and angles (Newcombe & Uttal, 2006). The use of a geometric map requires the child to either mentally or physically rotate the map so it is in the same orientation as the actual physical space (Spelke, Gilmore, & McCarthy, 2011). Alternatively, a child could successfully use a geometric map by extracting the map’s geometric properties and comparing them to the physical space.

A study of spontaneous use of geometric cues examined 4-year-olds’ ability to use geometric cues to place an object in a simplified spatial layout (Shusterman, Lee, & Spelke, 2008). Geo- metric cues illustrate the spatial relationships between objects using information such as the distance and angle between objects. As depicted in Figure 5.8, children were exposed to three types of spatial arrangements of identical objects. Children stood in a specific location in the room and were given a map of the room. They were instructed, “This picture tells us where Froggy wants to sit. Can you put Froggy where he wants to go?” The map allowed children to use either egocentric cues (locations relative to child) or allocentric cues (locations relative to other locations). Children were given three practice trials with only two objects in the room. Their ability to use geometry to put Froggy in the correct location in the test trials required them to select from among three locations. Children performed well on the linear and right triangle arrangements, particularly in the egocentric condition (Shusterman, et al., 2008; see also Uttal, Sandstrom, & Newcombe, 2006).

Section 5.5Spatial and Geometric Concepts in Childhood

Figure 5.8: Maps used to assess children’s understanding of geometric cues

Children were asked to place Froggy in the location marked on a map, which provided either egocentric or allocentric cues. Children selected the correct locations more frequently using egocentric cues than allocentric cues.

Source: Adapted from Shusterman, A., Lee, S., & Spelke, E. S. (2008). Young children’s spontaneous use of geometry in maps. Developmental Science, 11(2), F1–F7.

These results show that 4-year-olds can spontaneously use some geometric cues to place or locate objects in a room with no formal instruction. In particular, they were able to use dis- tance to locate objects in the linear display. Whether they could use angle information was unclear, because in the right triangle condition children could rely on distance (Shusterman et al., 2008). Subsequent research has shown that kindergartners can use angle information to place objects in correct locations (Spelke et al., 2011).

Section 5.5Spatial and Geometric Concepts in Childhood

Spotlight on Research: Core Knowledge of Geometry in an Amazonian Indigene Group One of the questions pertaining to children’s development of spatial and geometric concepts is the origin of this knowledge. According to the core knowledge perspective, certain aspects of geometric concepts are a property of the human mind and have an evolutionary history (Dil- lon, Huang, & Spelke, 2013). Thus, this understanding is universal and should be present in all cultures regardless of experiences.

In a study of the children and adults of the Mundurku group, an indigene group in a remote area of the Amazon, spatial understanding was examined. Participants from age 6 years to adulthood were assessed on basic principles of Euclidean geometry, including understanding of points, lines, parallel lines, geometric shapes, and other principles. They were shown sets that each contained six shapes or forms, one of which did not match the others. For example, a set might contain one triangle among five quadrilaterals. The participants were asked to identify which shape or form did not belong.

There were no differences in performance between the children and Mundurku adults. Par- ticipants performed well on most concepts except the geometrical transformations (identify- ing mirror images of shapes). A comparison group of children and adults in the United States were also tested. There were no differences between the children from either culture. The U.S. adults, however, performed significantly higher than the Mundurku adults.

The Mundurku participants were also tested on their ability to use landmark cues as well as different map orientations as a direct test of geometrical knowledge. They were given a map of the location of a hidden object. Locating the objects required an understanding of the geo- metrical relationship among the items. As with the first task, children and adults from both cultures performed significantly above chance level. The children from both cultures and the Mundurku adults performed at similar levels, whereas the U.S. adults performed better.

Particularly intriguing about these findings are the cultural differences between the Mundurku and U.S. participants. Specifically, the Mundurku group had no formal education or experience with maps, and their language has minimal words for labeling spatial relationships. Despite these differences, performance was remarkably similar—particularly for the children and the Mundurku adults. These findings suggest that a basic understanding of geometry develops separately from language, experience, or teaching and may be a core domain (Dahaene, Izard, Pica, & Spelke, 2006). However, for more abstract geometrical concepts, formal education is required. The higher performance of the U.S. adults suggests that education contributes to the further enhancement of the core knowledge principles of geometry that are shared by all humans.

Critical-Thinking Question

The study’s authors argue that because the Mundurku had similar spatial reasoning as par- ticipants in the United States, this implies that spatial concepts are an innate property of the human mind. What is an alternative way to explain this similarity in spatial reasoning without relying on innate geometric knowledge?

Section 5.5Spatial and Geometric Concepts in Childhood

Map-reading skills continue to develop across childhood and adulthood (Liben, 2009). Most of the research examining map reading in young children has been conducted in small-scale environments, such as a room. However, people often need to use maps to navigate large- scale environments. Watching people trying to make their way around an amusement park illustrates some of the difficulties in following a map in a large-scale environment.

A study of 9- to 10-year-olds examined their ability to use a map to navigate around an unfa- miliar campus. Children were asked to indicate on the map the location of the flags they encountered. A computer-based navigational task was also created to mimic the real-world map task (Liben et al., 2013).

Of particular interest was whether differences in map-reading ability were related to perfor- mance of three measures of spatial cognition:

1. Spatial perception: the ability to spatially orient the environment in relation to the self

2. Mental rotation: mentally imaging how two- and three-dimensional objects would appear after they are rotated

3. Spatial visualization: solving problems using verbal and visual information to fold a paper in specified ways (Liben et al., 2013).

Children varied in how well they located the flags. Researchers were interested in whether these differences in map reading were related to performance on the three measures of spa- tial perception. The relationship between the spatial battery tasks and map reading received some support. Children’s performance on the map task was related to their overall spatial scores. That is, better scores on map reading were related to better spatial cognition. Examin- ing the specific spatial tasks showed different patterns. Visual perspective taking was related to map reading as well, whereas mental rotation was not. Similar performance on map-read- ing and spatial skills were found in the computer task. One implication is that spatial cogni- tive skills for navigating large-scale environments can be taught in the classroom by using technology to simulate such an environment (Liben et al., 2013).

Social Construction of Spatial Concepts As we described for biological concepts, children’s interactions with teachers and parents contribute to their understanding of spatial concepts. In a joint book-reading task, parents were asked to read wordless picture books that highlighted different spatial relationships to their 3- to 5-year-old children. One type of spatial relationship was that of distance, in which the same object was portrayed from different distances. That is, the image of an object will vary depending on the distance it is from the observer. The children of parents who empha- sized these spatial relationships in the book-reading task did better on tests of spatial under- standing (Szechter & Liben, 2004).

An example of these conversations is illustrated below:

Parent (P): (on p. 5) Can you find the rooster on this page (P flips back to p. 4 and then returns to p. 5)?

Section 5.5Spatial and Geometric Concepts in Childhood

P: Not quite huh? You can see the boy and the girl (P points at the boy and girl). We’re getting further away from the rooster, huh?…

P: (on p. 10). Where did we start? Do you remember? Where’s the rooster?

Child (C): (C points to the magazine cover at the farm building)

P: Down in the barnyard. All right.…

P: (on p. 12) So where did we start, do you remember where the rooster was? In the barnyard.

C: (C points to the magazine cover)

P: Way, way down in there (points to the cover) wasn’t it? We can’t see … it’s too little now, that’s where we started (P turns to p. 13). (Szechter & Liben, 2004, p. 875)

In this example, the parent is pointing out spatial relations across pages. This research is another good example of the social construction of knowledge. This is a form of interaction or teaching that preschool teachers could employ to help children acquire various spatial concepts.

The emergence of children’s spatial and geometric understanding is similar to the develop- ment of biological concepts. As for most topics, there are various theoretical positions to explain the emergence of spatial concepts. Piaget’s constructivist account was the first to describe the development of different types of spatial concepts. Recent accounts have tended to adopt a core knowledge perspective (Spelke, Lee, & Izard, 2010). As with the description of other core knowledge domains, these systems represent conceptual primitives that are avail- able to our species. They provide the foundation by which formal and additional geometric knowledge is constructed through both experience and education through the use of human symbolic systems (Spelke et al., 2010). However, some argue that this initial knowledge of space or biology is not needed, but rather is acquired through domain-general mechanisms of experience and education (Sloutsky, 2010; Tarlowski, 2006).

Education and Geometry Spatial and geometric concepts are crucial for learning mathematics. Einstein, the most prominent physicist of the previous century, stated that geometry was central to his theoretical breakthroughs in physics. Intriguingly, his interest in geometry began in childhood (Clements & Sarama, 2011).

However, geometry is often ignored in children’s early education (Clements & Sarama, 2011). Further, for- mal assessments of students’ geometry understand- ing show considerable low achievement among some students. To enhance children’s concepts of geometry,

Questions to Consider

1. Generate other activities that might be effective in teaching children geometric concepts. Explain how these activities would be engaging and meaningful for children.

2. How might you get fellow students to work together to generate this understanding?

Summary and Resources

teachers are encouraged to incorporate geometry in the early education curriculum (Sarama & Clements, 2013).

Table 5.3 provides examples of classroom activities to teach geometric concepts to preschool- ers and kindergartners.

Table 5.3: Preschool and kindergarten classroom activities to teach geometry concepts

Concept Goal Task

Shape identification Identifying squares, rectangles, tri- angles, and rhombuses

Given a large selection of manipula- tives, select all the exemplars of the stated shape.

Shape composition Composing and decomposing shapes Choose the shape that would result if a shape was cut.

Congruence Matching congruent shapes Given eight shapes, identify pairs that are the same shape and same size.

Construction of shape Building a shape from its components Can you make a triangle using some of the straws?

Turns Recognizing rotation Analogy (A:B:C:?) with objects rotated 90°

Measurement Measuring length Which of these strings is about the same length as four cubes?

Patterning Copying and extending Copy and extend an ABAB shape pattern.

Source: Clements & Sarama, 2007, p. 14.

Summary and Resources

Chapter Summary

• Concepts are fundamental to human cognition because of their use in many forms of thinking, such as problem solving, categorization, and inductive inferences.

• The classic view of concepts represents concepts by a set of necessary and sufficient features.

• The probabilistic view of concepts proposes that exemplars of concepts are com- pared to a prototype based on family resemblance or similarity.

• The theory view of concepts argues that explanatory principles, such as an object’s origins, are a component of conceptual representation.

• Infants progress from forming superordinate or global categories to basic cat- egories to subordinate levels. Older children and adults prefer the basic level of categorization.

• Preschool children, age 5 years and under, have difficulty understanding class inclu- sion, the idea that lower level concepts are included in higher level concepts.

Summary and Resources

• Children around age 3 to 4 years begin to make conceptual distinctions between natural kinds and artifacts.

• Children make inductive inferences about nonobvious properties of biological con- cepts, reflecting an understanding of psychological essentialism.

• Children’s experience with nature and with expert adults enhances their under- standing of biology and makes their inferences more selective.

• Children have a bias to attend to biologically relevant information. This is initially reflected in infant preferences for human faces and biological motion. Children also reason differently for biological concepts; for example, they make inductive infer- ences for nonobvious properties.

• There is a neural basis for face processing involving the right hemisphere that becomes more evident with development. Children with autism show selective defi- cits in face processing and some understanding of biological concepts.

• Spatial concepts show similar developmental patterns to biological concepts. Young children have some understanding of spatial relations, which provides a foundation for geometry and mathematics.

• Map reading requires an understanding of geometric relationships between the elements of the map and the environment. Children improve in their ability to use geometric cues to locate objects in space.

• Children’s ability to understand many geometric concepts does not depend on for- mal education or speaking a language that has many spatial terms.

• Both biological and spatial concepts are influenced by experience and teaching.

Posttest Questions

1. According to which theory are concepts represented by a set of necessary and suf- ficient features?

a. probabilistic theory b. prototype theory c. classical view d. theory view

2. The probabilistic view of conceptual representation indicates that .

a. children have explanatory principles for identifying the purpose of different features

b. concepts are represented by a prototype or best example c. all category exemplars have the same set of principles d. categories are used for inductive inferences

3. Which level of categorization develops last in infancy?

a. superordinate b. basic c. subordinate d. global

Summary and Resources

4. During a class-inclusion experiment, a child is shown five apples and nine bananas and asked, “Are there more bananas or more fruits?” At which stage will the child say there are more bananas?

a. Formal operational b. Sensorimotor c. Concrete operational d. Preoperational

5. According to the naive theory (folk biology) view, if taught a new property about a known animal, 5-year-olds rely on to make their inferences.

a. categorical membership b. perceptual similarity c. experience with the animal d. gender

6. A child asked to teach another child a new concept selects a diverse sample compo- sition to do so. Which type of learning does this reflect?

a. pedagogical learning b. social constructivism c. nonpedagogical learning d. Piagetian constructivism

7. Children with autism are LEAST likely to pay attention to what part of the face?

a. eyes b. mouth c. chin d. ears

8. Functional magnetic resonance imaging studies indicate that specialized regions of the brain develop last for which type of concept?

a. objects b. faces c. scenes d. biological motion

9. Comparisons of Mundurku children’s understanding of spatial concepts showed .

a. a lack of understanding b. poorer performance than U.S. children c. better performance than U.S. children d. equal performance to U.S. children

10. If a child is able to rely on spatial relationship such as angles, lines, and distance to locate objects depicted on a map, he or she shows an understanding of .

a. geometric correspondence b. representational correspondence c. dual representation d. symbolic relationships

Summary and Resources

Critical-Thinking Questions

1. Do the findings that certain concepts may reflect a core knowledge domain have implications for how children should be taught about that concept? How would you create a learning environment to optimize these biases? Would teaching differ for concepts that do not reflect innate biases?

2. In the current chapter, we focused on particular concepts. Think of another con- ceptual domain that is important to children’s education (such as time). Then apply what you have learned about conceptual organization and development and describe that concept. How would you teach a kindergartner about that concept?

Key Terms

artifacts Objects created by humans, including tools and furniture.

artificialism A Piagetian description of preoperational children’s belief that natural phenomena such as the sun are produced by humans.

autism A neurodevelopmental disorder characterized by rigid, repetitive behavior and impaired social interactions and com- munication skills.

basic level The preferred level of categoriz- ing objects due the perceptual distinctive- ness between basic-level categories.

categories A grouping of different exam- ples of a concept.

classical view The perspective of concep- tual representation that proposes that con- cepts have a set of necessary and sufficient features.

class inclusion The understanding that a particular category belongs to a larger category.

concepts Mental representations of the objects and ideas of the world.

Euclidean space The ability to mark the positions of an object relative to an external frame of reference metrically using vertical and reference axis. Develops during the pre- and concrete-operational periods.

family resemblance A measure of similar- ity among category exemplars in terms of the number of features they share.

folk biology A naive theory view of the domain of biology, such as the properties of living entities.

folk physics A naive theory view of the domain of physics, such as the properties of objects and their movements through space.

geometric correspondences Spatial links between the location of a symbol on a map and the location of the referent in the real world.

geometric cues The use of information such as distance and angle to represent the spatial relationships between objects in order to locate objects in the real world using a map.

global categories A synonym for superor- dinate categories; this term is often used to describe infants’ and toddlers’ categories.

Summary and Resources

inductive inference The process of mak- ing a generalization or an evidence-based hypothesis. In the case of concepts, it reflects the process of generalizing known facts about a concept to new elements of the same concept.

lexical concept A concept labeled by a sin- gle word that is related to a discrete entity.

naive theories A version of the theory view of concepts that argues that for core domains such as biology and physics, chil- dren’s understanding can be represented by a theory that provides explanatory prin- ciples and identifies entities within that domain.

natural kinds Objects found in nature, including animals, plants, and minerals.

nonpedagogical learning Learning in which learners discover information for themselves through observation or inference.

pedagogical learning Learning in which information is intentionally communicated to the learner by a teacher or other knowl- edgeable person.

pedagogical sampling The selection of a range of exemplars to teach a new concept.

perceptual concepts Concepts based on physical appearance.

projective space The relative position of different objects in relation to a single observer and not the actual distances of objects. It develops during the preopera- tional period of age 2 to 6 or 7 years.

prosopagnosia “Face blindness” charac- terized by an inability to recognize faces of family members or famous individuals.

prototypes The best example of a concept used to represent the concept.

psychological essentialism The belief held by children and adults that categories have an underlying reality that accurately depicts the natural world.

representational correspondences The understanding that symbols on a map cor- respond to real-world referents. A line on a map, for example, represents an existing road.

similarity-induction perspective The view that children’s categorical inductions rely on perceptual similarity among category examples up until around age 7 years.

subordinate level The lowest and most specific level of a categorization hierarchy.

superordinate level The highest and most general level of categorization hierarchy.

Additional Resources Web Resources

Annenberg Learner http://www.learner.org This site provides resources for teaching wide-ranging concepts from kindergarten through adulthood.

Autism Speaks http://www.autismspeaks.org/what-autism This site offers a wealth of information on children with autism, including diagnosis and treatment.

Summary and Resources

Laboratory for Developmental Studies, Harvard University http://www.wjh.harvard.edu/~lds/index.html?spelke.html Elizabeth Spelke’s website at Harvard University includes several video interviews of her discussing her research on concepts and gender.

Further Reading

Donovan, J., & Venville, G. (2012). Exploring the influence of the mass media on primary students’ conceptual understanding of genetics. Education 3-13, 40(1), 75–95. This article explores students’ understanding of scientific concepts such as genetics based on exposure to mass media.

Lourenco, S. F., Addy, D., Huttenlocher, J., & Fabian, L. (2011). Early sex differences in weighting geometric cues. Developmental Science, 14(6), 1365–1378. doi:10.1111/ j.1467-7687.2011.01086.x The authors examine whether there are gender differences in spatial ability and when they appear.

Answers and Rejoinders to Chapter 5 Pretest

1. False. Although children do use appearance to identify concepts, they can also use nonperceptual information such as knowledge of an animal’s internal parts to deter- mine what type of animal it is.

2. True. Children and adults prefer to use basic-level terms that most easily capture concepts at a level that is not too broad (animal) or too narrow (eagle).

3. True. Infants show a preference for looking at animate things, such as biological motion.

4. False. Children with autism avoid looking at faces, particularly the eyes. 5. False. Young children not yet attending school and people from cultures without for-

mal instruction do understand some basic elements of geometry. Formal education is necessary to understand complex concepts of geometry.

Answers and Rejoinders to Chapter 5 Posttest

1. c. classical view The classical view defines concepts by a set of necessary and sufficient features. Although this approach is accurate for well-defined concepts, it is too limited to describe many concept examples.

2. b. concepts are represented by a prototype or best example The probabilistic view argues that concepts are represented by a prototype. Dif- ferent exemplars of the concepts vary in family resemblance or similarity to the prototype.

3. c. subordinate The subordinate level is the most specific and develops last because one must distinguish it from very similar exemplars. Conceptual development during infancy progresses from global to basic to subordinate.

4. c. Concrete operational Piaget argues that children need to understand the logical relationship among the hierarchy levels to pass the class-inclusion tasks. This understanding first becomes available in the concrete-operational child.

Summary and Resources

5. a. categorical membership Children rely on categorical membership to make their inferences.

6. a. pedagogical learning In pedagogical learning, children asked to teach a concept will select the diverse sample to optimize learning. This form is less important for discovery activities.

7. a. eyes Children with autism tend to ignore the eyes and other socially relevant information.

8. b. faces Specific brain activity for faces develops in adolescence, whereas brain regions for the other stimuli occur much earlier.

9. d. equal performance to U.S. children Children were equal in performance even though their cultural experiences were dif- ferent. These results suggest that some geometric concepts reflect a core knowledge domain.

10. a. geometric correspondence The use of these cues reflects geometric correspondence. Children can transfer the geometric relationships between the location of objects in the map to the environment.