FIGURE 1.1 These animals are going to the farm.
The plane from San Francisco to Atlanta was crowded, with every seat filled. Tina (age 3½) was seated in the middle of a three-seat row, with her dad in the window seat and an older adult in the aisle seat. While the plane was boarding and taxiing for takeoff, Tina was talkative and wiggly and it seemed like this long flight would be very tedious for her. While her dad was getting her settled, she kept pointing to his iPad™, which he had put in the seat pocket and he reminded Tina a number of times that she would have to wait to get that until after the plane was in the air. Once the plane was on the way, he pulled out two little pink ear buds and put them in Tina’s ears and then put the iPad on a Disney movie. Tina sat quietly in her seat absorbed in the movie for most of the rest of the trip. She did eat a snack and, during the last half hour of the trip, she dozed off. However, the iPad movie engaged her attention for over 2 hours! Her dad had very little talk with his daughter after the iPad took over.
Studies of the dynamic relationship among brain developmental processes, child and adolescent play experiences, and the influences of technology-augmented play materials are only in initial stages. However, it is likely that play development and brain development may be differentially affected by play with technology-augmented materials. What brain development effects will occur due to humans’ pervasive interactions with technologically advanced materials is not a new question, however, as various theorists and researchers have speculated on it in the past.
For example, in pondering the course of cognitive growth and the reasons for the human evolution of large brains, Bruner (1964) drew attention to a paper written on the one hundredth anniversary of Darwin’s (1859) publication of The Origin of the Species in which the authors asserted that the brain’s development has occurred because of the “result of a technical-social life” (Washburn & Howell, 1960, p. 49).
Bruner proposed that intellectual functioning has always been driven by “a series of technological advances in the use of mind” (p. 1), which enabled humans to manage in increasingly complex environments and “construct models of their world” (ibid.). He hypothesized that over the long evolutionary period, humans have increased their intellectual power by learning to use and understand three types of technological artifacts: amplifiers of human motor capabilities (e.g., wheels, bicycles), amplifiers of sensory capacities (e.g., radios, magnets), and amplifiers of human ratiocinative capacities (e.g., language and other symbol systems)—all of which are transmitted by the culture in which humans live. Each of these has a “mode of representation” (p. 2). Enactive representation occurs through motor responses, which are the earliest mode of understanding. For example, young children’s tricycle riding or block building involves motoric interactions with the environment and encodes knowledge in the muscles, and this knowledge can then be applied to other actions in the environment. Iconic representations involve the organization of images or models and the understanding that such pictures or images of perceptual events can “stand for” the actual environmental features. This is evident when a young child can point to a picture of “shoe” or “kitten” or find the “truck” or the “car” in a storybook. Symbolic representation begins when children can use an arbitrary symbol system such as language or numbers to encode meaning. This occurs when a child knows the symbol “Bill” stands for his name or can point to the symbol “3” to show how old he is. Once these modes of representation are learned, humans can produce combinations of images or actions that go beyond “real-world” experiences. In Bruner’s view, this ability to “become specialized by the use of technological implements” (p. 2) has made the evolution of human abilities possible. If new technological artifacts give humans different interactive experiences, then future evolution of the human species through interaction with present day and future technologies is a definite possibility.
The role playfulness may serve in fostering human brain and cognitive development has been of interest to various theorists such as Plato, who in his book of Laws (360 BC) suggested that children’s play (paidia) had significance as a venue for learning and developing basic habits of character (paideia) (see Morris, 1998). At later time periods, the view that children’s playful activity has educational and developmental meaning was emphasized by many theorists, including Comenius (1632, 1657), Rousseau (1792/1911), Froebel (1887), Dewey (1910, 1916), and Hall, (1920, 1924). In the mid-20th century, Huizinga (1950) wrote that playfulness is an integral behavior of the human species and thus he called humans Homo Ludens (“man, the player”). Huizinga’s view of the evolutionary importance of play was also discussed by Ellis (1998), who asserted that playful behaviors positively influence the ability of biological systems to exhibit rapid adaptation when unpredictable events that threaten survival are encountered. Human existence has always been precarious and he suggests it is likely that humans who had the greatest range of adaptive behaviors to meet changing environmental or social conditions (i.e., the most playful humans) were the ones who were most likely to survive. In his view, that is why and how present humans have inherited their intensely playful qualities.
Researchers who have studied play in animals also have lent insights into possible play-brain connections. For example, Lorenz (1971) indicated that, for many animal species, the curiosity young animals exhibit in their play is a characteristic needed for expressing new behaviors in varied settings. He compared the play of children to the research of adult scientists. Fagen (1981), who wrote extensively about animal play, agreed, stating that such play is essentially “a biological adaptation for producing novel behaviors” (p. 36). Recently, researchers using brain imaging techniques with animals have studied how the “playful brain” evolved in both animal and human species. (Iwaniuk et al., 2001; Pellis & Iwaniuk, 2004). Their research shows that animals with larger brains compared to their body size also exhibit the most playfulness. Relevant to the question of technology-augmented play effects, Whiting and Pope Edwards (1988), after conducting cross-cultural studies of children’s play, concluded that the types of play in which children engage are malleable due to social and cultural messages, thus reflecting the cultural meanings of the society in which it occurs. If this is the case, then the present day cultural messages promoted through technology-augmented play may make this the preferred type of play for young humans in the 21st century. Freysinger (2006), in discussing play throughout the life span, states that the types of human play that are exhibited are “situated in a specific historical time and the economic, political, religious, and social reality of the day” (p. 60). In a recent discussion of cultural neuroscience theory, Kitayama (2013) has explained that, because of the brain’s neuroplasticity, brain activity patterns may differ when varied culturally sanctioned behaviors are elicited. Thus, it is possible that the play behaviors promoted in a technologically pervasive culture will have a lasting impact on children’s brain structures and functions.
Although they did not tie play behaviors to specific areas of the brain, two prominent theorists who did describe specific developmental relationships between various types of play and cognitive growth are Piaget (1945, 1965) and Vygotsky (1962, 1967). From observations of his own children’s play in infancy and his study of older boys’ marble game play, Piaget closely linked the various stages of play development to the growth of cognitive and moral abilities. His view was that children used play to construct their knowledge of the world by trying to relate their new experiences to their existing cognitive schema and their developing thought processes. Vygotsky investigated ways that children’s play fostered learning of their cultural language and he stated that, especially when children engage in pretend play, their spontaneous concept development is fostered, leading to growth in self-regulation and development of internal modes of thought.
These earlier perspectives on the potential role of play in affecting brain maturation and the development of human capabilities provide the background for present investigations, because, if, as these theorists have asserted, human survival skills, cultural meanings, and cognitive advancement are all linked to playful behaviors, then the types of play in which children and adolescents are engaging at the present time are likely to affect their cognitive and social-emotional development, their adaptability to meet cultural demands, and even their survival in the world of the future. That is why the question of how the changing play environment may both positively and negatively affect brain development and subsequent behavior adaptability for children and adolescents is of interest, as is the question of the potential effects of such technology-augmented play on the broader society of the future. Because the brain maturation process provides many opportunities for environmental affordances such as play materials and technological artifacts to affect the nature of the adult brain, it is important to understand the brain maturation process (Bergen & Coscia, 2001). A glossary with a list of definitional terms related to the brain and diagrams of basic brain and nervous system areas are included in the appendix.
In the late 20th and early 21st century, information regarding how the brains of humans and other creatures operate has grown exponentially, due to the invention of research techniques that can observe both the electrical and chemical processes occurring in the brain at various ages as well as the expansion of synaptic connections and subsequent pruning of neuronal structures from birth to adulthood. Because over 71% of human brain development occurs after birth and brain maturation continues until about age 20, the experiences children and adolescents have (including their play experiences!) profoundly affect the ways their individual brains are structured and, consequentially, the ways they will perform throughout the rest of life. Researchers have found some differences in the adult brains of various individuals who have pursued certain careers. While the brain does retain some plasticity throughout life and later experiences may affect brain structures and functions, there is no question that the experiences of the first 20 years of life have the greatest impact in determining which areas of the brain are more densely formed and activated and which areas are pruned more precisely before the brain reaches its mature state. The consensus of researchers is that both individual genetic and experiential factors are crucial in determining brain structure and function in adulthood. As the Hindu phase “Sarvam annam” reminds us, for the developing human brain, “everything is food.”
The sequence of brain development in infants and young children has been well charted by researchers during the past 20 years. At birth, the neonate already has about 100 billion neurons, which were created during the prenatal stage. The neuron has three major parts, a cell body, dendrites that receive information, and axons that transmit information. These neurons compose the majority of those that the individual will have throughout life, but many of them are not yet connected in neural networks. Only those needed for essential life processes are connected firmly at birth so the process of synaptogenesis (creating neuronal network connections) is of great importance during the first few years of life. If the brain is well nourished and adequately stimulated, each neuron can produce up to 15,000 synapses (Lezak et al. 2004) during early development. The brain’s weight increases from about 1 pound at birth to 2 pounds by 1 year, partly due to the increase in synapses and partly due to the coating of nerve axons with fatty glial cells (myelination), which act to speed neural signals. Research has shown that the brain stem and cerebellum begin myelination first, before the cerebral areas, and that myelination of the frontal lobes continues into adolescence.
The occipital (visual) lobe of the cortex is one of the first parts of the brain that has rapid synaptic growth and, therefore, this is one of the first areas in which pruning (the loss of nonessential connections) takes place. This is why treatment for young children with vision difficulties usually takes place at an early age before the pruning process in the visual cortex is highly active. Synaptogenesis also is especially active during the first years in the parietal lobe of the cortex (motor and sensory brain areas), and this synaptic growth is clearly seen in the increasing sensory and motor behavioral skills that children develop in the first years of life enabling them to demonstrate “enactive” cognition.
Social development is promoted by the activation of “mirror neurons,” located in the premotor cortex, which connects portions of the parietal lobe with the occipital lobe and various other areas in the cortical regions (Rizzolatti & Craighero, 2004). The function of these neurons seems to be to enable infants to transform visual information into understanding of the actions of others by engaging them in the imitation of the observed behavioral acts. This infant understanding usually occurs first in interaction with parents or others in their social world, but young children’s understanding of the actions of objects (e.g., toys) also seems to be derived from this mirror neuron system (Bergen & Woodin, 2010). In Bruner’s terms, this ability also may be related to the “enactive” mode of thought. When the infant is about 6 months old, synaptogenesis also begins to increase between the limbic system, which contains the autonomic and emotion centers, and the frontal lobe of the cortex, which involves higher thinking processes. Although young infants have many emotional reactions, their ability to understand and label these emotions is not well developed until the synaptic connections between the limbic system and the cortex increase. When these connections are more strongly established during the toddler and preschool years, children can begin to use “iconic” and “symbolic” levels of thought.
The toddler years are a time of great brain activity because synaptogenesis expansion is greatest at that time, and by age 3 the child’s brain has about 1,000 trillion connections, which is twice the density of the adult brain (Shore, 1997). The toddler brain is about two and a half times as active as the adult brain because it is not as efficient as the adult brain. The weight of the brain continues to increase due to the rapid expansion of synapses and the myelination of the axons and by the age of 6, the child’s brain has about 90% of its adult weight. Synaptogenesis in the frontal lobe is most prominent during the latter part of early childhood, and the frontal lobe has the greatest synaptic density at about age 7. Because pruning of each area begins when synaptic density reaches its highest point, pruning in the frontal lobe begins in earnest in middle and later childhood. Pruning results in greater efficiency and thus, from age 3 to 8, children’s speed of processing, memory activity, and problem-solving skills are increasing. The P300 wave, which is related to attention, problem-solving abilities, and speed of processing, begins to be observed at about age 7 (Eliot, 1999). Thus, less brain energy (glucose) is burned as the brain becomes more efficient (Haier, 1993). During this 3–8 age period individualization of the brain also becomes more evident as the structures and functions interact with environmental experiences. According to Eliot (1999), “once a given brain region has passed the refinement stage, its critical period has ended, and the opportunity to rewire it is significantly limited” (p. 38).
During the later elementary age period (8–12), the brain continues to mature, especially in the frontal lobe areas. For example, the dorso-lateral prefrontal cortex, which is involved in monitoring executive functioning skills, is made more efficient through pruning nonessential neural connections (Bauer et al., 2010). The neural circuits that an individual has used less frequently are the ones most likely to be pruned and, although such pruning increases speed of processing, the pruning also results in less flexibility to restructure brain areas. This process of individualization of brain structures is often apparent in the narrowing of activity and learning choices that children make in late elementary and middle childhood (Bergen & Coscia, 2001). During this period the brain increases its ability to use “iconic” and “symbolic” methods of representing thought.
Recent research on the adolescent brain has discovered how much more brain maturation is still occurring during the years from 12 to 20. During middle childhood (12–14) young adolescents still use a larger area of the brain than adults do to carry out discrimination tasks because the maturation of the frontal lobe is still occurring. Myelination continues, glucose use declines, and pruning is extensive. By middle childhood, there is evidence of stable brain differences; however, areas related to executive functioning are still not mature. Research comparing adolescent and adult parietal, temporal, and occipital areas of the brain show that they are relatively similar, which indicates that those brain areas have reached a relatively mature state. In contrast, adolescent frontal lobes, which are the site of executive functioning skills, are not as mature as those of adults. All three of the thought systems described by Bruner (i.e., enactive, iconic, and symbolic) are well established, however. Although the adolescent has more advanced thinking and reasoning skills, there is still much development occurring and “the implication of these changes are not well established” (Bronk, 2010, p. 49). During adolescence another area of the brain is still maturing. That is the limbic system, which is involved in learning, memory, and emotions. For example, the adolescent brain shows continuing maturation of the amygdala, which perceives and interprets emotions; the insula, which is involved in emotions and risk-taking decisions and behaviors; and the hippocampus, which is involved in emotional, learning, and memory reactivity (Baird et al., 1999).
Longitudinal studies of brain development from childhood to adulthood show that the volume of gray matter (involved in synaptogenesis and pruning) increases and decreases in various areas of the brain in relation to the maturation of those areas, but that the volume of white matter (the myelin coatings) continues to increase until the third decade of life (Giedd & Rapoport, 2010). These researchers noted that female brains appear to reach peak periods of maturation slightly earlier than male brains, and hormonal changes in males and females also have been shown to affect brain functioning, especially in the limbic and frontal lobe areas. In a comparison of 12–16 year olds and 23–30 year olds, Sowell et al. (1999) concluded that the reported reduction in gray matter (connective tissue) occurring between adolescence and adulthood was a reflection of myelination that still was continuing after the teen years in peripheral regions of the cortex, which improved cognitive functioning into adulthood. Because brain maturation is a long process that is not fully completed until early adulthood, the play experiences of adolescents continue to be an important influence.
According to theorists and researchers who have studied how play develops, the most common type of play seen in infancy, usually called practice play, involves repeating activities with increasing elaboration or difficulty and this type of play is very evident in the first year of life. Typically, infants and young children first will try to see what a particular object does when they interact with it, but soon they begin to play with the object; that is, they try to find many ways to interact with the object. As Hutt (1971) states, first children find out what an object does and then they explore what they can do with the object. She calls the first activity “exploration” and the second “play.” Practice play is one way that Bruner’s “enactive” mode of cognition is demonstrated. Social practice play also occurs in infant interaction with parents, siblings, and other individuals in a kind of “turn-taking” model. A good example of this is the “peek-a-boo” play routine that engages child and adult, and, although initially initiated by the adult, it is quickly taken over by the child, who controls the “peeks,” with increasingly great laughter. Repetition with elaboration occurs not only with people and objects but also with language and musical sounds, and provides increasingly child-controlled playful interactions.
By the end of the first year of life, usually with an initial demonstration by adult or older child, pretense begins. Young children begin to act “as if” in their play by pretending that objects have social meanings and engaging in short social scripts. For example, “drinking” milk from an empty cup, “feeding” a doll with imaginary food, or “talking” on the phone are often the first evidences of such pretense. In relation to Bruner’s cognitive schema, being able to treat appropriately a replica object as a real object (e.g., use driving motions with a plastic or wooden “car” or hugging a doll “baby”) is an early example of the “iconic” mode of cognition. In pretense the “play frame” (Bateson, 1956) is understood even by young children and they begin to demonstrate their ability to respond to a language label or action demonstration that shows the symbolic meaning given to the objects used in the play. When the language label itself prompts a particular action, for example, acting the role of “mommy” or “doctor,” in Bruner’s terms, they are now able to demonstrate a “symbolic” mode of cognition. Pretense becomes increasingly elaborated over the next 5 years, and it is often observed as the major play mode of children during the toddler and preschool years. Elaborated pretense involves child-controlled scripts, roles, and scenes, both reality and fantasy based. Children use whatever experiential material is available, drawing on their life experiences or from books, television, and other media. Vygotsky (1967) has explained how the elaborated scripts that are used in pretense challenge children to act in roles that require varied social skills that may be above their present level of development and thus such pretense promotes both cognitive and social development.
In the elementary-age period, pretense continues to be a major play mode but is not as obvious to observers since it often involves small-scale dolls or action figures, elaborated but private settings, and detailed scripts that may take many days to be played out. In studies of adults’ memories of their childhood play, adults often report examples of this type of pretense, which involves constructing the design of the “set” in which the pretense will occur (Bergen, 2009). Such “small-worlds” play has been reported by many McArthur Fellows as a major play mode of their youth (Root-Bernstein & Root-Bernstein, 2006). This set building is a mature form of construction, which involves play with building materials such as blocks and replica small-scale objects (e g., toy animals, figures, trucks). This type of play becomes prominent during the preschool age period. The difference between such construction play and actual construction is that the playfulness in the act of constructing is important (Forman, 2006). In contrast to construction that is made to last, in playful construction the designs change constantly and, once built, these constructions are as easily destroyed by the children in order to build another different world with the same materials. Children experiment with objects and other materials to learn more about the laws that operate in the physical world, and their constructions have dynamic system qualities. Pretense is often combined with construction play; that is, the “set” is designed in which the pretense occurs.
According to Piaget, the ability to play games-with-rules requires other sets of skills that involve social, cognitive, and moral decision making. Usually older toddlers can play one-rule games such as peek-a-boo or hide and find, but the elaboration period for games with rules begins in later preschool and becomes a major type of play during the elementary-age years. Most early games have only one or two rules and these rules can change often, depending on the players’ skills and interests. Games with rules are evident in board games and in the type of outdoor games of the “child culture” that have been cataloged by researchers (Opie & Opie, 1969). The difference between such games and activities called “sports” is that games with rules are controlled by children and involve adapting or changing rules in collaboration with other children in order to make the game more “fair” or more “fun.” The types of board games that are usually played by children or families are also similar to games with rules because often the rules are adapted for younger children. For example, they might get extra turns or the goal of the game may not be to win but for all to finish together.
In addition to Bruner, Piaget, and Vygotsky, there are many other theorists and researchers who have discussed the potential relationships among various types of play and child progress in specific developmental areas. In particular, the role of pretense in fostering social, emotional, language, and cognitive abilities has been discussed extensively and research studies examining various aspects of play that seem to be related to developmental growth have been proposed by numerous authors, although the evidence is mixed (Lillard et al. 2012).
Beginning in the mid-20th century (see Parten, 1933), observational studies of children’s social development during play have been conducted. Parten’s early studies described the typical social stages of play that can be observed in preschool children, which seemed to indicate developmental progress. For example, children typically progress from playing alone in parallel situations with other children and later engage in elaborated socially complex play scenarios. Smilansky (1968) conducted studies to observe whether growth in such skills could occur during sociodramatic play and found that both social pretense and language skills could be developed. Rubin and colleagues (Rubin, 1985; Coplan, Rubin, & Findlay, 2006) have reported that children who do not progress from solitary play to social play may have developmental difficulties at later ages, and authors have discussed how complex pretense scripts require children to understand roles and the behaviors required in various roles (e.g., Ariel, 2002; Vandenberg, 2004). Games with rules also have socio-moral components that must be addressed by children during their competitive game playing (DeVries, 2006).
The assertion that play has a role in supporting emotional health has a long history. Erikson (1977), Anna Freud (1928), and many others concerned with mental health issues of children have promoted the use of play therapy to assist children in gaining emotional control and healing. Also, therapists such as Greenspan (1990) have developed “floor-time” play techniques for parents and children with autistic spectrum disabilities. Although there are not as many studies specifically related to the role of play in assisting typically developing children’s emotional development, Lillard et al. (2012) report that the studies that have been reported do indicate emotion regulation may be improved through pretend play. Vygotsky’s view of elaborated pretense as a means of developing self-regulation skills has also been supported by research (see Bordrova & Leong, 2006).
As noted earlier, Piaget (1965) described the role of games with rules as being involved in promoting children’s moral development, especially in their moral reasoning. DeVries (2006), drawing on the work of Kohlberg (1987), has specifically investigated the moral dilemmas that arise when children play games together and has documented the issues that arise in such play. Recently Davis and Bergen (2014) have discussed the types and levels of moral development that college-age individuals report and compared those levels to the types of play that they reported at various age levels. They found that earlier pretend play, as well as games, appeared to be related to higher levels of moral development at college age.
There are proponents of the view that cognitive development is highly related to play, especially to pretense, and there have been many studies that have reported relationships between play and various cognitive processes. For example, Russ (2013) makes the case for childhood pretense being the foundation for adult creativity, Roskos and Christie (2004) discuss how pretend play increases literacy development, Kamii et al. (2004) report how block building supports mathematical understanding, and Cooper and Robinson (1989) indicate the extent that certain types of childhood play is related to science and engineering careers.
The potential role of “embodied cognition,” in which physical actions serve as a venue for thought, has been discussed by a number of theorists (see review by Wilson, 2002). From this theoretical perspective the workings of the human mind can be understood in the context of its interactive relationship to human bodily actions. This perspective suggests that the mind/body interactive connection is essential for human development because perceptual and motoric processing were the initiators of cognitive activity in evolutionary history. Whether such “embodied cognition” is an essential element for human development is being debated and it will be tested as technology-augmented play that does not require extensive bodily movement becomes more and more pervasive.
Recently play development and brain maturation, as well as other developmental processes, have been characterized as nonlinear dynamic systems (Bergen, 2012; Fromberg, 2010; Vanderven, 2006). According to Guastello (1997), this perspective on human development is concerned with the analysis of the ways in which living systems show complex nonlinear dynamics that interact with other such systems and thus increase in complexity of interaction. Thelen and Smith (1994) have stated that nonlinear dynamic systems theory is the appropriate way to study human development processes because development is “modular, heterochronic, context-dependent, and multidimensional” (p. 121). Play development and brain maturation, as well as other developmental processes, exemplify many of the characteristics of nonlinear dynamic systems. They are complex phenomena that have not been well explained by linear systems thinking (van Geert, 2000).
Nonlinear dynamic systems theory, derived from fields such as biology, physics and mathematics, posits that changes over time among interrelated elements have complex and systematic interactions. The features of the theory that have relevance for human development systems have been outlined by Thelen and Smith (1994). They state that human development systems have multiple and continuous interactions at levels from molecular to cultural and these unfold over many time scales. Dynamic systems are multilayered and complex and their actions and interactions cannot be explained by linear, simple cause/effect research. Therefore, when studying the effects of particular phenomena (such as the effects of technology-augmented play materials on human development), the characteristics of the dynamic system must be considered. These are some of the characteristics of such systems that have been identified by Thelen (for further details, see Bergen, 2008, 2012). Such systems are:
Brain research has provided evidence that brain development follows a nonlinear systems model (Bates, 2005). Even in the prenatal period, the brain shows self-organization, with patterns that spontaneously emerge from chaotic appearances. For example, during this period, the cortex is formed by neurons climbing “ladders” of glia cells to create the higher brain centers (Bergen & Coscia, 2001). Sensitive dependence on initial conditions is also evident, as research on the harmful effects of drugs or alcohol on the prenatal brain and abuse or neglect effects on infant brain development has shown (Perry, 1996; Carlson & Earls, 1997; Eliot, 1999). However, the brain also shows openness, receiving energy from outside sources as well as having control parameters that guide the developmental patterns of various parts of the brain. Some parameters are invariant (sensory locations), some change with age (frontal lobe development), and some change with experiences (synaptic connections). Behavioral evidence of phase shifts in brain development can be seen in the change in infant emotion and language once myelination begins to connect the limbic system with the frontal lobe. Although the brain is modular, with certain areas having some primary roles, it is also interdependent. Soft assembly is also a characteristic of the brain because it is flexible, with stable and dynamic qualities alternating; it is not “hard-wired.” Thus, a primary characteristic of the brain is that of plasticity, because the capacity for brain system change is always present. There are periods of both attractor states and periods of disequilibrium. Recursion is also present in the brain because brain development is repetitive, with elaborations both across brain areas and across developmental age in self-similar patterns. The fractal quality can be seen in the repeating patterns of development as each area of the brain becomes activated, and in the nested quality of many brain functions.
Play development also meets dynamic systems criteria. Play is a self-organizing system that may appear chaotic but that moves toward order, involving spontaneously emerging patterns of attractor states. Play involves phase shifts, which are abrupt changes in play patterns that lead to higher levels of play, but the play state also shows disequilibrium, because it is always capable of change. Play usually has recursive elements with elaborations and self-similar patterns within each developmental age. These systems of repeated patterns are often labeled “practice play.” Play also exemplifies the characteristic of sensitive dependence on initial conditions because small inputs into play situations may cause disparate results. The types of materials, the time available for play, the settings in which it can occur, and the materials available all influence the character of pretense. Play demonstrates openness because the players continue to receive energy from sources outside the “playframe” (Bateson, 1956). It also involves control parameters, such as differences in play patterns due to age and skill of players, limitations on experience, types of settings available for play, and player-defined rules in games. Play shows interdependence because all levels of play are interrelated and because of its soft assembly, play has both stable and dynamic alternating periods and thus is not “hard-wired.” Play epitomizes plasticity because capacity for change is always present. Thus, play also can be characterized as a nonlinear dynamic system.
There are many ways that typical playful behavior at various ages reflects maturation of certain brain areas. For example, during the infant period, as the sensorimotor areas of the brain develop, infants enjoy looking and reaching for objects, hearing and making interesting sounds, and engaging in exploratory play. When sensory and motor areas gain greater synaptic connections, practice play involving repeating and elaborating on actions becomes the most common play type. Piaget saw this practice play as evidence of “thought in action” and Bruner would agree that this shows “enactive” thought. As the emotional brain centers begin to connect to frontal lobe brain areas, social-emotional play, such as peek-a-boo and other turn-taking games begin. At the end of the first year, when the higher brain centers where language and conceptual thought are primarily located begin to mature, play with language and pretend play begin.
Toddler play reflects the continuing development of the frontal cortex, the site of symbolic thought, through their initiation of such pretense, which becomes a major play mode by age 3. Studies of the concept “theory of mind” (ability to imagine what others are thinking) have indicated that toddlers demonstrate that first in pretense and older toddlers are able to implement simple scripts with two or three action elements. Although practice play remains a major mode, it often has elements of construction and pretense. For example, a “garage” for a car might be made with a few blocks. Another element of brain maturation is shown in toddler language play and expressions of humor, which result from observing or performing incongruous events, such as putting a hat on a dog figure.
By early childhood, sociodramatic pretense involving elaborate scripts and set designs appear and games with rules become more complex. Construction involves designing settings for play as well as creating art and designs. There is a great deal of discussion of “fair” rules in games and there are many symbolic games that children play. Practice play continues to be prominent, with bike riding, skating, and other tests of skill of prime interest. These more elaborate manifestations of play give evidence of the synaptogenic and pruning processes occurring during this age period. During middle childhood the extensive and elaborative private pretense, which may involve sets and scripts that continue for many weeks, also gives evidence to the refining of brain structures and functions. Practice play, however, may be more in the service of sports at this age, for example, repeatedly shooting baskets into the net on the garage wall. Many elements of play first seen in middle childhood are continued in adolescence, such as risk-taking physical activities such as rope climbing and playing elaborate symbolic games. Although sports may take the place of most play for some adolescents, many adolescents engage in fantasy pretense (daydreaming, writing poetry, composing music) and enjoy performing in actual plays or having hobbies such as collecting sports figures. Many of the risk-taking types of playful activities in which adolescents engage give evidence that limbic and frontal lobe maturation is not yet completed.
Whether and how the presence of technology-augmented play materials may differentially affect these dynamic interactions of brain maturation and play development are unclear, however. Before evaluating the potential ways technology-augmented toys can affect various areas of human development, it is important to consider the many meanings the term “technology” has embraced.
The definitions of the meanings and connotations of technology range from simple to complex. For example, the Encyclopedia Britannica provides a broad but accessible definition of technology, as “the application of scientific knowledge to the practical aims of human life or, as it is sometimes phrased, to the change and manipulation of the human environment” (www.britannica.com). There are other perspectives that capture the scope and variability of the concept, however. For example, Heidegger (1977) argued that technology is a way of thinking that reveals an essence of efficiency for its own sake. According to Heidegger, technology should not be defined just by its instrumental purposes because then “we remain held fast in the will to master it” (p. 32). We should have a broader definition and move beyond values such as efficiency. Batteau (2009, 2010) delineated between “tools” and “technology,” and argued that technology embraces increasing complexity, autonomy, and connectedness. He embedded technology firmly within “sociotechnical networks” (Batteau, 2009, p. 11) and suggested that technology could not exist outside the frame of the networks because of its effect on culture and culture’s effect on technology.
Another theorist, Arthur (2009) defined technology in three ways: 1) “a means to fulfill a human purpose,” 2) “an assemblage of practices and components,” and 3) “a collection of devices and engineering practices available to a culture” (p. 28). For Arthur, this definition was critical because he asserted that how humans think of technology will determine how they think of its creation. Feenberg (2006), however, argued for a definition of technology that spans two dimensions, namely values and agency. Technology can be seen as either value-neutral or value-laden and either autonomous or humanly controlled. Feenberg suggests that humans will “inevitably address the question of technology along with many other questions that hang in suspense today” (p. 15). However, Poster (2001) asserts that “the term technology is particularly misleading in the age of ‘smart machines’ ” (p. 21). The only modifier for technology, “high technology,” refers to advanced assemblages of machines but it “does not distinguish clearly between particular types such as mechanical or electrical” (p. 21). Although the definitions of technology are complex, the definition used in this book is closer to the generally accepted and accessible definitions. That is, the authors suggest that technology-augmented play materials apply “scientific knowledge” to human play experiences and involve the “change and manipulation of the human environment.”
Human technological invention and discovery also have the characteristic qualities of nonlinear dynamic systems. For example, although inventors initially have some type of plan in mind, much of technological change results from self-organizing aspects inherent in the technological systems, which have chaotic as well as ordered qualities. There are periods of systematic discovery in which inventions have emerging patterns of attractor states that dominate. However, there are also phase shifts, in which abrupt changes in technological thought lead to extensions and differentiations in technological creations. Therefore, technology development also shows disequilibrium, because it is always capable of change. New technological inventions usually have recursive elements that involve elaborations of similar patterns drawn from earlier ideas. Technology invention also exemplifies the characteristic of sensitive dependence on initial conditions because small inputs into a technological process may cause disparate new materials or products. The types of materials, the time and support for technological invention, the settings in which it can occur, and the materials available all influence the character of technological creativity and invention. These also demonstrate openness because those involved in technology invention receive energy from many sources outside the existing frames of understanding and soft assembly, because technological creativity has both stable and dynamic alternating periods. Technological invention epitomizes system plasticity because the capacity for change is always present. Of course, there are also control parameters that depend on differences in past technological knowledge, the creativity and skill of inventors, limitations in their experience, the types of settings available for invention, and the openness of the cultural system to new technological ideas. Thus, technological invention demonstrates interdependence because there are many levels of interaction.
The dynamic interactions of technology-augmented toys and devices—such as “talking” toys, video games, and phone apps—with brain development and with play development are likely to affect the domain-general capacity of the neurally plastic brain, resulting in “pluripotentiality” (Bates, 2005) of possibilities. Cortical structures can be configured in many ways, depending on types and timing of experiences, which enable the brain to adapt to a variety of different “brain plans.” Research on the nature of play has shown that it also exemplifies pluripotentiality, continually adapting to environmental conditions and developmental changes (Vanderven, 2006). Because the play environment for children and adolescents has changed greatly with the advent of technology-augmented play materials, all of the dynamic system factors that have affected brain and play interactions with traditional play materials are now also being affected by technology-augmented play materials. Since brain maturation is influenced by whatever experiences the individual encounters, it is likely that changes in child and adolescent play experiences will differentially interact with brain maturation factors, resulting in “future brains” that differ from those humans have today. These factors will also affect the development of social, emotional, moral, and cognitive abilities, which will exhibit pluripotentiality in future generations.
FIGURE 1.1 These animals are going to the farm.
FIGURE 1.2 I’m talking to mommy.
FIGURE 1.3 Can the dolls go into the doll house?
FIGURE 1.4 This is my favorite hat!
2. Talk to your parents or other people in your family about their remembrances of their play experiences. What ways are they different from those of yours and your friends? How do you think they may have affected their brain maturation and subsequent behaviors?
3. Read the book, The Velveteen Rabbit (Williams-Bianco, 1926). Write a paragraph about what you think the author was trying to express about the developmental meaning of such traditional, non-technology-augmented toys. Speculate about how technology-augmented toys could or could not have the same developmental meaning.
Ariel, S. (2002). Children’s imaginative play: A visit to wonderland. Westport, CN: Praeger.
Arthur, W. B. (2009). The nature of technology: What it is and how it evolves. New York: Simon and Schuster.
Baird, A. A., Gruber, S. A., Fein, D. A., Maas, L. C., Steingard, R. J., & Renshaw, J. F. (1999). Functional magnetic resonance imaging of facial affect recognition in children and adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 2, 195–199.
Bates, E. (2005). Plasticity, localization, and language development. In S. T. Parker, J. Langer, C. Milbrath (Eds.), Biology and knowledge revisited: From neurogenesis to psychogenesis (pp. 205–254). New York: Psychology Press.
Bateson, G. (1956). The message “This is play.” In B. Schaffner (Ed.), Group processes: Transactions of the second conference (pp. 145–241). New York: Josiah Macy, Jr. Foundation.
Batteau, A. W. (2009). Technology and culture. Long Grove, IL: Waveland Press.
Batteau, A. W. (2010). Technological peripheralization. Science, Technology, and Human Values, 35(4), 554–574.
Bauer, P. J., Lukowski, A. F., & Pathman, T. (2010). Neuropsychology of middle childhood development (6 to 11 years old). In A. Davis (Ed.), Handbook of pediatric neuropsychology (pp. 37–46). New York: Springer.
Bergen, D. (2008). Human development: Traditional and contemporary theories. Upper Saddle River, NJ: Pearson/Prentice-Hall.
Bergen, D. (2009). Play as the learning medium for future scientists, mathematicians, and engineers. American Journal of Play, 1(4), 1–10.
Bergen, D. (2012). Play, technology toy affordances, and brain development: Considering research and policy issues. In S. Waite-Stupiansky & L. Cohen (Eds.), Play: A polyphony of research, theories and issues (Volume 12) (pp. 163–174). Lanham, MD: Information Age.
Bergen, D., & Coscia, J. M. (2001). Brain research and childhood education: Implications for educators. Olney, MD: Association for Childhood Education International. [Translated and published in China, 2006]
Bergen, D., & Woodin, M. (2010). Neuropsychological development of newborns, infants, and toddlers (0–3). In A. Davis (Ed.), Handbook of pediatric neuropsychology (pp. 13–30). New York: Springer.
Bordrova, E., & Leong, D. J. (2006). Adult influences on play: The Vygotskian approach. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve: Contexts, perspectives, and meanings (2nd ed., pp. 167–172). New York: Routledge.
Bronk, K. C. (2010). Neuropsychology of adolescent development (12 to 18 years). In A. Davis, (Ed.), Handbook of pediatric neuropsychology (pp. 45–57). New York: Springer.
Bruner, J. S. (1964). The course of cognitive growth. American Psychologist, 19(1), 1–15.
Carlson, M., & Earls, F. (1997). Psychological and neuroendocrinolgical sequelae of early social deprivation in institutionalized children in Romania. In C. S. Carter, I. I. Lederhendler, & B. Kirkpatrick (Eds.), The integrative neurobiology of affiliation (pp. 419–428). New York: New York Academy of Sciences.
Comenius, J. A. (1632/1907). Didactic magna. London: A. C. Black.
Comenius, J. A. (1657/1967). Orbis pictus. London: Oxford University Press.
Cooper, S., & Robinson, D. A. (1989). The influence of gender and anxiety on mathematics performance. Journal of College Student Development, 30(5), 459–461.
Coplan, R. J., Rubin, K. H., & Findlay, L. C. (2006). Social and nonsocial play. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve: Contexts, perspectives, and meanings (2nd ed., pp. 87–102). New York: Routledge.
Darwin, C. (1859). The origin of species. Reprint. New York: Modern Library.
Davis, D., & Bergen, D. (2014). Relationships among play behaviors reported by college students and their responses to moral issues: A pilot study. Journal of Research in Childhood Education, 28, 484–498.
DeVries, R. (2006). Games with rules. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve: Contexts, perspectives, and meanings (2nd ed., pp. 119–126). New York: Routledge.
Dewey, J. (1910/1997). How we think. Toronto: Dover.
Dewey, J. (1916). Democracy and education. New York: Macmillan.
Eliot, L. (1999). What’s going on in there: How the brain and mind develop in the first five years of life. New York: Bantam.
Ellis, M. J. (1998). Play and the origin of the species. In D. Bergen (Ed.) Readings from Play as a learning medium (pp. 29–31). Olney, MD: ACEI.
Erikson, E. H. (1977). Toys and reason. New York: Norton.
Fagen, R. (1981). Animal play behavior. Oxford: Oxford University Press.
Feenberg, A. (2006). What is philosophy of technology? In J. R. Dakers (Ed.), Defining technological literacy: Towards an epistemological framework (pp. 5–16). New York: Palgrave Macmillan.
Forman, G. (2006). Constructive play. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve: Contexts, perspectives, and meanings (2nd ed., pp. 103–110). New York: Routledge.
Freud, A. (1928). Introduction to the techniques of child analysis. New York: Nervous and Mental Disease Publishing.
Freysinger, V. (2006). Play in the context of life-span human development. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve: Contexts, perspectives, and meanings (2nd ed., pp. 53–62). New York: Routledge.
Froebel, F. (1887). The education of man. New York: Appleton-Century.
Fromberg, D. P. (2010). How nonlinear systems inform meaning and early education. Nonlinear Dynamics, Psychology, and Life Sciences, 14(1), 47–68.
Giedd, J. N., & Rapoport, J. L. (2010). Structural MRI of pediatric brain development: What have we learned and where are we going? Neuron, 67(5), 728–734.
Greenspan, S. I. (1990). How emotional development relates to learning. In S. Hanna & S. Wilford (Eds.), Floor time: Tuning in to each child (pp. 1–4). New York: Scholastic.
Guastello, S. J. (1997). Science evolves: An introduction to nonlinear dynamics, psychology, and life sciences. Nonlinear Dynamics, Psychology, and Life Sciences, 1(1), 1–6.
Haier, J. (1993). Cerebral glucose metabolism and intelligence. In P. A. Vernon (Ed.), Biological approaches to the study of human intelligence (pp. 317–332). Norwood, NJ: Ablex.
Hall, G. S. (1920). Youth. New York: Appleton-Century.
Hall, G. S. (1924). Adolescence: Its psychology and its relations to physiology, anthropology, sociology, sex, crime, religion and education. New York: D. Appleton.
Heidegger, M. (1977). The question of technology and other essays. Trans. W. Lovett. New York: Harper and Row.
Huizinga, J. (1950). Homo Ludens: A study of the play-element in culture. London: Routledge & Kegan Paul.
Hutt, C. (1971). Exploration and play in children. In R. E. Herron & B. Sutton-Smith (Eds.), Child’s play (pp. 231–252). New York: Wiley.
Iwaniuk, A. N., Nelson, J. E., & Pellis, S. M. (2001). Do big-brained animals play more? Comparative analysis of play and relative brain size in mammals. Journal of Comparative Psychology, 115(1), 29–41.
Kamii, C., Miyakawa, Y., & Kato, Y. (2004). The development of logico-mathematical knowledge in a block building activity at ages 1–4. Journal of Research in Childhood Education, 19(1), 44–57.
Kitayama, S. (2013). Mapping mindsets: The world of cultural neuroscience. Observer, 26(10), 21–23.
Kohlberg, L. (1987). Child psychology and childhood education: A cognitive-developmental view. New York: Longman.
Lezak, M. D., Howieson, D. B., & Loring, D. W. (2004). Neuropsychological assessment (4th ed.). New York: Oxford.
Lillard, A. S., Lerner, M. D., Hopkins, E. J., Dore, R. A., Smith, E. D., & Palmquist, C. M. (2012). The impact of pretend play on children’s development: A review of the evidence. Psychological Bulletin. Advance online publication.
Lorenz, K. (1971). Studies in animal and human behavior. New York: Methuen.
Morris, S. R. (1998). No learning by coercion: Paidia and Paideia in Platonic philosophy. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve and beyond: Contexts, perspectives, and meanings (pp. 109–118). New York: Garland.
Opie, I., & Opie, P. (1969). Children’s play in streets and playgrounds. London: Clarendon Press.
Parten, M. (1933). Social play among preschool children. Journal of Abnormal and Social Psychology, 28, 136–147.
Pellis, S. M., & Iwaniuk, A. N. (2004). Evolving a playful brain: A levels of control approach. International Journal of Comparative Psychology, 17, 92–118.
Perry, B. (1996). Incubated in terror: Neurodevelopmental factors in the “cycle of violence.” In J. D. Osofsky (Ed.), Children, youth, and violence: Searching for solutions (pp. 2–20), New York: Guildford.
Piaget, J. (1945). Play, dreams and imitation in childhood. London: Heinemann.
Piaget, J. (1965). The moral judgment of the child. New York: Norton.
Plato. (360 BC).Laws, (1942) translator R. G. Bury London: Heinemann.
Poster, M. (2001). What’s the matter with the internet? (Vol. 3). University of Minnesota Press.
Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 27, 169–192.
Root-Bernstein, M. M., & Root-Bernstein, R. S. (2006). Imaginary worldplay in childhood and maturity and its impact on adult creativity. Creativity Research Journal, 18, 402–425.
Roskos, K., & Christie, J. (2004). Examining the play-literacy interface: A critical review and future directions. In E. Zigler, D. Singer, & S. Bishop-Josef (Eds.), Children’s play: The roots of reading (pp. 95–123). Washington, DC: Zero to Three Press.
Rousseau, J. J. (1792/1911). Emile. New York: E. P. Dutton.
Rubin, K. H. (1985). Nonsocial play in preschoolers: Necessary evil? Child Development, 53, 651–657.
Russ, S. W. (2013). Pretend play in childhood: Foundation of adult creativity. Washington, DC: American Psychological Association.
Shore, R. (1997). Rethinking the brain: New insights into early development. New York: Families and Work Institute.
Smilansky, S. (1968). The effects of sociodramatic play on disadvantaged preschool children. New York: Wiley.
Sowell, E. R., Thompson, P. M., Holmes, C. J., Jernigan, T. L., & Toga, A. W. (1999). In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nature Neuroscience, 2(10), 859–861.
Technology (n.d.). In Encyclopedia Britannica. Available at: www.britannica.com
Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. Boston: MIT Press.
Vandenberg, B. (2004). Real and not real: A vital developmental dichotomy. In E. Zigler, D. Singer, & S. Bishop-Josef (Eds.), Children’s play; The roots of reading (pp. 49–58). Washington, DC: Zero to Three Press.
Vanderven, K. (2006). Play, proteus, and paradox: Education for a chaotic and supersymmetric world. In D. P. Fromberg & D. Bergen (Eds.), Play from birth to twelve and beyond: Contexts, perspectives, and meanings (2nd ed., pp. 405–516). New York: Garland.
van Geert, P. (2000). The dynamics of general developmental mechanisms: From Piaget and Vygotsky to dynamic systems models. Current Directions in Psychological Science, 9, 64–88.
Vygotsky, L. S. (1962). Thought and language. Cambridge, MA: MIT Press.
Vygotsky, L. S. (1967). Play and its role in the mental development of the child. Soviet Psychology, 5, 6–18.
Washburn, S. L., & Howell, F. C. (1960). Human evolution and culture. In S. Tax & C. Callendar (Eds.), The evolution of man (Vol. 2). Chicago: University of Chicago Press.
Whiting, B., & Pope Edwards, C. (1988). Children of different worlds: The formation of social behavior. Cambridge, MA: Harvard University Press.
Williams-Bianco, M. (1926). The velveteen rabbit: or, How toys become real. Pioneer Drama Service, Inc.
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636.