Child computer Interaction Theory

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Child-Computer Interaction Juan Pablo Hourcade Chapter 1 Introduction What is child-computer interaction? Child-computer interaction concerns the study of the design, evaluation, and implementation of interactive computer systems for children, and the wider impact of technology on children and society. This definition, paraphrasing the Association for Computing Machinery’s (ACM) definition of human-computer interaction, lists design, evaluation and implementation in an order in which they normally do not occur. This is intentional, as most human- and child-computer interaction research is about design, followed by evaluation, followed by implementation. Child-computer interaction is gaining in importance as computers increasingly play a ubiquitous role in our lives, including the lives of children. Children in high-income regions of the world are now growing up expecting items they encounter to be interactive, and content of their choice to be immediately available. It is likely that children in low-income regions will experience the same even before they have access to basic services such as sanitation. As children grow up using interactive computer devices more frequently, the way they learn, play, and interact with others is changing. Whether the changes that occur are positive or negative will depend on how these interactions with computers are designed, and how these devices are used. Child-computer interaction is the field that studies how to design interactive technology for children, and how children may make the most out of it in order to have the most positive impact on their development. How is child-computer interaction different from adult-computer interaction? Read and Bekker (2011) suggested the following key differences: the rate of change of children when compared to adults, the frequent involvement of adults in children’s interactions with technology (the opposite is not true), the different contexts of use, and the underlying cultural and societal values with regard to what is good for children. A brief history of the field As computers rose to prominence after World War II, their use centered on military, business, and scientific applications. In the 1960s and 1970s, a group of pioneering researchers including Seymour Papert, Marvin Minsky, and Alan Kay began exploring the design of computer systems for children. Their original focus was making computer programming accessible to children, but in the long term, their work had broad influences, including early tablet and laptop design ideas, the development of object-oriented programming, and a vision for the use of computers in education (Kay & Goldberg, 1977; Papert, 1993). These pioneers were not alone in their interest in expanding the use of computers to a wider audience. An interdisciplinary group of researchers including computer scientists, psychologists, 1 and engineers slowly began forming what is now known as the human-computer interaction field, focusing on methods for design, implementation, and evaluation of interactive computing systems. Encouraged by the release of IBM’s Personal Computer in 1981, they began organizing the Human Factors in Computing Systems (CHI) conference 1982, beginning as an official Association for Computing Machinery (ACM) conference in 1983. After sprinkles of work influenced by both traditions in the 1980s, a more steady flow of research in child-computer interaction began in the 1990s, with growing influences from education, developmental psychology, graphic design, and communication studies. This movement coalesced with the first Interaction Design and Children (IDC) conference, organized in 2002. Since then, this annual conference has been the center for child-computer interaction research. While its foundation came largely from the human-computer interaction field, over the years it has incorporated work from researchers who typically publish in education and media studies venues. Yarosh et al. (2011) published the most recent analysis of trends at the conference. The 10 pillars of child-computer interaction As the child-computer interaction field matures, some guidelines for success have emerged, some well established in the field, others still in their nascent stage. They provide lessons on how and what to design. Work in interdisciplinary teams These days, interactive technologies for children are most often created by design teams instead of individuals. The most successful projects tend to have interdisciplinary teams, or at the very least, involve people experienced in design and evaluation methods, technology builders (e.g., computer scientists, engineers), and experts in the particular child population being targeted (e.g., children, parents, teachers, psychologists, educators). In addition, most teams include a designer (graphic or industrial), and experts in the topics the technology touches (e.g., if it is digital library software, a librarian). Deeply engage with stakeholders The design process to create an interactive computer system involves a series of steps, from setting requirements, to establishing designs, implementing technologies, and evaluating them. Deeply engaging with key stakeholders during the design process significantly increases the chances that a technology will be successful. As adults, not only do we have difficulty remembering what it was like to be children, but we have to realize that each generation of children has its own views, expectations, and experience with technology, as well as its own needs and interests. For this reason it is important to involve children throughout the design process. Just like human-computer interaction researchers and practitioners call for user- centered design, in the child-computer interaction field, we value child-centered design. Children are not the only ones affected by the technologies they use; caregivers and other adults with whom children interact, such as teachers, should also play a role in the design process. Likewise, it is often not sufficient to meet stakeholders; there is also a need to learn about their daily realities and the contexts in which technologies are likely to be used. 2 As a rule of thumb, the less familiar the design team is with the stakeholders and the contexts in which they will use technology, the more deeply it should engage with them. An overview of design and evaluation methods that can be used to facilitate this engagement is provided in Chapter 6. Evaluate impact over time Children usually do not change immediately when they use technology. In fact, skills and abilities emerge over time (see Chapter 2 under Computationally and biologically-inspired theories), so to truly understand the impact of technology we need to see how it affects children over an extended period. Out of the ten pillars of child-computer interaction, this is the one that is currently implemented the least, mostly due to limited budgets to evaluate technologies. Design the ecology, not just the technology Technology use is significantly affected by context. For this reason, when designing technologies for children, it is important to not just think of the technology, but to take into account the broader context of use. In addition, design teams can go further and design the whole ecology of use. In other words, do not stop at the technology, but instead design the physical space where it will be used, and perhaps even think about the people who may be present when the technology is used, and the supportive activities. For more information on this approach see Chapter 6 and its section titled Ecological approaches. Make it practical for children’s reality For a technology designed for children to be successful, it needs to be able to work in children’s real contexts. While it is often necessary to start the design process in a lab, designs should consider, from the beginning, the contexts in which children are likely to use technology, and whether it is fit for these contexts. Fragile, heavy, uncomfortable, flimsy, or dangerous designs are unlikely to make an impact. Likewise, technologies should be relevant to children’s lives, needs, and interests. Personalize Children arrive at the use of technologies having gone through different life experiences, with a different set of skills, neural structures, and bodies. Their needs and interests are diverse. Some may have cognitive, motor, or perceptual impairments. For this reason, personalization can provide great benefits in making technology advantageous for children. It is important to point out that this is even more important for children than for adults, as younger children are more likely to show greater diversity in needs and abilities when compared to older children and adults. Be mindful of skill hierarchies In many domains, including music and education, the learning process consists of learning basic skills, and then adding more complex skills that are based on the first set. Design teams need to be mindful of the skills necessary for using an interactive technology, and ensure that the children who will use the technology have those basic skills. If children are learning skills through technology, then again, skill hierarchies should be noted. For more information see 3 section on Behaviorism under Chapter 2. Support creativity Learning can be more motivating if it is done with a purpose meaningful to the child, such as creating or building. This idea forms the basis of the concept of constructionism, Seymour Papert’s view on child development that has had great influence on the field of child-computer interaction (more on this in Chapter 2). Papert’s work and his most direct influences have been on enabling children to program computers, with outcomes they can relate to, whether it is drawings in the Logo programming language or robots made out of LEGO bricks with LEGO Mindstorms. This focus has been greatly expanded in the child-computing interaction community with interactive technologies now supporting a wide variety of other creative activities including storytelling, music authoring, three-dimensional design, smart textiles, and so forth (see Chapter 7 for examples). Augment human connections Secure attachments to parents and primary caregivers are paramount to children’s positive development. Likewise, face-to-face interactions with teachers, friends, and other peers are a foundation for the learning and development of critical skills, such as listening, negotiating, sharing, teaching, and helping others. Read more about the importance of human connections in Chapter 2 under Sociocultural approaches. While computers can often interfere with these personal connections, they can also augment them. Within child-computer interaction, there has also been a significant amount of attention paid to communication and collaboration technologies, with many including support for face-to- face collaboration most recently through touchscreen, tangible, and full-body user interfaces. There has also been a recent surge in technologies to support remote communication, mostly with the aim of keeping children in contact with close family. See Chapter 8 for more examples of research in this area. Enable open-ended, physical play Children who participate in open-ended, physical play can benefit in many ways, including having better health, developing problem-solving skills and resiliency, learning to engage with peers, negotiating, and advocating for themselves (read more in Chapter 2). The child-computer interaction community has worked on supporting this form of play, with many examples of computer-enhanced indoor and outdoor physical play in Chapter 11 under Promoting healthy lifestyles. Overview of the book The rest of the book is divided in four sections. The first section provides background on children’s development and the risks and opportunities associated with technologies. Chapter 2 covers child development and discusses the best known theories and concepts from developmental psychology and how they apply to child-computer interaction. Chapter 3 discusses the risks that technology may bring children and how to avoid them. 4 The following section provides more background on basic concepts from human-computer interaction and how they apply to child-computer interaction. Chapter 4 defines usability for children, including a discussion of user experience and usability goals. Chapter 5 provides an overview of usability principles and heuristics by revisiting guidelines for adults from a child’s perspective. Chapter 6 is an introduction to design and evaluation methods that includes a review of lifecycle models, an overview of methods based on children’s roles, followed by more detailed examples of activities that can be conducted at each step of the design process. The next section is a literature review of research in child-computer interaction, organized by topic. Chapter 7 presents research on creativity and problem solving, including programming, storytelling technologies, and “maker movement” enabling technologies. Chapter 8 includes research on collaboration and communication, including a discussion of technologies to support face-to-face activities, as well as those designed to support remote communication. Chapter 9 is about experiencing media and includes research on search engines, digital libraries, and interacting with digital content. Chapter 10’s topic is learning, including a review of research on interactive technologies designed for children to learn science, mathematics, reading, writing, and other topics. It also includes a discussion of overall strategies for the design of learning applications and the challenges of bringing computers to schools. Chapter 11 covers research on technologies to promote health, and to help children with special needs. These include technologies to promote healthy lifestyles, assist children with specific health conditions (e.g., diabetes), and support children with special needs (e.g., children diagnosed with autism spectrum conditions). The last section of the book consists only of Chapter 12, which is a look at the future of child- computer interaction. It includes a discussion of possible risks ahead, remedies for these risks, as well as research challenges for the child-computer interaction community to grow as a field and make a stronger, more positive impact on society. Summary Child-computer interaction concerns the study of the design, evaluation, and implementation of interactive computer systems for children, and major phenomena surrounding them. As children grow up using interactive computer devices more frequently, the way they learn, play, and interact with others is changing. Whether the changes that occur are positive or negative will depend on how these interactions with computers are designed, and how these devices are used. Child-computer interaction is the field focused on how to design interactive technology for children, and how children may make the most out of it in order to have the most positive impact on their development. Child-computer interaction rose out of the work of Seymour Papert and his colleagues on making computer programming accessible to children, and the field of human-computer interaction. It has since counted with significant contributions from other fields including education, developmental psychology, and media studies. Since 2002, the annual Interaction Design and Children (IDC) conference has been the epicenter of child-computer interaction research. 5 As the field has matured, specific approaches have emerged as best practices. These constitute the ten pillars of child-computer interaction: work in interdisciplinary teams, deeply engage with stakeholders, evaluate impact over time, design the ecology not just the technology, make it practical for children’s reality, personalize, be mindful of skill hierarchies, support creativity, augment human connections, and enable open-ended, physical play. 6 Chapter 2 Child Development To understand how to best design technology for children, we must first consider existing research on child development. Child development is a dramatic, highly-complex process that we are only beginning to understand. For example, children typically acquire more than 60 thousand words in their first 18 years of life (Bloom, 2002), each with its own sound pattern, spelling, and meaning. Children also rapidly improve in motor abilities, and (when given the opportunity) are often able to handwrite, type, and play a musical instrument by the time they complete elementary school (Nichols, 1996; Klinedinst, 1991). These improvements are also reflected in children’s ability to use input devices (Hourcade et al., 2004; Anthony et al., 2012; Hourcade et al., 2015). Other cognitive improvements are exemplified by Kail’s (2000) model of changes in reaction times and information processing speed. This rapid pace of development is accompanied by a high amount of within- and between-child variability (Siegler, 2007). This high rate of change and high variability is one of the key differences between children and adults that needs to be taken into account when designing interactive technologies (Read and Bekker, 2011). Children develop through bidirectional interactions that go from genetic activity, to neural activity, to behavior, to the environment, and back (see Figure 1). The greater the flexibility at each layer, the more adaptable children’s development. The place where computers play a role is in mediating (together with the body) the interactions between behavior and environment. Indeed, computers are arguably the most flexible, malleable, and powerful tools people have ever had available. To understand how to best influence these developmental changes, designers need to consider the child development literature to make it more likely that children can change in healthy ways while using technologies, and that these technologies are appropriate for children’s needs, abilities, and interests. This chapter provides an overview of the child development literature while focusing on aspects that matter to the design of technology. It begins with theories of development that have had a significant impact on the field of child-computer interaction, including Piaget’s constructivism and its extension by Papert, and sociocultural theories inspired by Vygotsky. Both of these approaches provide the foundations for more recent theories, such as neuroconstructivism, connectionism, and dynamic state theories that provide stronger connections to the biology of the brain. The chapter continues with a discussion on theories of intelligence and how to measure it, as well as of skills, such as executive function and emotional intelligence, that can help improve performance in school and on intelligence tests. 7 Figure 1. Bidirectional influences on development (Gottlieb, 1991). Piaget and constructivism Jean Piaget was arguably among the most influential experts on child development during the 20th century. His work continues to have a significant influence on developmental psychology and educational research, while his views on how children learn have also affected the field of child-computer interaction. Below, three aspects of Piaget’s work are highlighted: how children construct knowledge through a process he called adaptation; the role of maturation, experience, social aspects, and emotional aspects in children’s development; and the developmental stages children go through as they develop. Adaptation, constructivism, and constructionism Piaget thought that learning occurs through a process of adaptation, in which children adapt to their environment. He saw this adaptation as an active process in which children construct knowledge structures by experiencing the world and interacting with it. This idea, referred to as constructivism, holds that children actively construct their own knowledge through experiences. The same experience will affect individual children in different ways, since they will come to it with different existing knowledge structures. This view stands in contrast with the idea that children simply store knowledge imparted by others and all perceive and learn from an experience in the same way. The basic Piagetian view of development is more consistent with more recent theories of child development, including neuroconstructivism, dynamic state theory, and connectionism, than is the passive view. 8 Seymour Papert, a key figure in the genesis of the field of child-computer interaction, expanded on Piaget’s ideas with his proposal for constructionism. Papert proposed that Piaget’s adaptation works best when children are “consciously engaged in constructing a public entity” (Papert & Harel, 1991). In other words, making something to share with others helps children construct knowledge. Papert extended Piaget’s concept of adaptation by placing a greater emphasis on the social and motivational aspects of learning, as well as on the importance of providing children with more opportunities to modify their environment, instead of just experiencing it. Papert’s ideas have had a great influence on the field of child-computer interaction. This is particularly clear in the emphasis on providing children with technologies with which they get to be authors, rather than experiencing worlds and situations that are pre-scripted, or absorbing facts provided by a computer. His influence also shows in the recurring focus on having children participate in designing the technologies that they use. In great part, Papert’s interest in computers for learning arose from the wide variety and complexity of entities children can construct using computers, which thus provide better learning opportunities and empower a shift from learning by being told to learning by doing. Papert also saw computers as a way of helping children connect their interests with subjects they may not otherwise enjoy (Kestenbaum, 2005). Factors affecting development Piaget cited four major factors that he thought affected development: maturation, experience, social aspects, and emotions. All four have a direct impact on how technologies for children should be designed. In the case of maturation, being aware of what most children are able to accomplish at a given age can provide interaction designers with useful guidelines. The other three factors are crucial in the design of educational technologies that can provide children with new experiences where they can interact with others as part of activities of interest (Piaget & Inhelder, 1969). Children’s physical maturation limits what and how they are able to learn. Piaget thought that while maturation certainly plays a role in learning, it does not guarantee that learning will occur. Rather, it limits what children can do (Piaget & Inhelder, 1969). As children grow up, their potential for learning increases. Hence, children’s limited cognitive and motor abilities will limit their ability to interact with technologies. This view on maturation needs to be taken in context of evidence that maturation, and in particular cognitive development, is affected by the environment in which children grow (Quartz & Sejnowski, 1997). In other words, while children’s maturation limits what they can do, the experiences they go through shape neural development and thus affect their development. Piaget viewed experience as a key factor in adaptation. Experiences are required for building knowledge structures (Piaget & Inhelder, 1969). This underlines the importance of learning about the world by experiencing it rather than being told about it, as Maria Montessori stressed (Montessori, 1964). Technologies can provide unprecedented experiences through their great malleability, enabling children to modify their environments and experience them in ways that were not previously possible. 9 Piaget thought that social interaction played a crucial role in development by enabling knowledge to be passed from one generation to the next (Piaget & Inhelder, 1969). The core of the contributions to this topic comes from sociocultural approaches to development that were pioneered by Lev Vygotsky (Vygotsky, 1978). We discuss these under Sociocultural approaches below. One important aspect of social interaction in development is that the knowledge that gets passed from one generation to the next is not just information, but strategies. In a panel at the IDC 2004 conference, Marvin Minsky and Alan Kay, both Turing Award recipients, highlighted the importance of learning by copying the way more knowledgeable and experienced people think and complete tasks. Kay made an interesting point when mentioning that when teachers assign something such as a composition and they do not do it themselves, they are indirectly telling children that it is not interesting. Computers can help in this respect by making links between passionate interests and powerful ideas not only for children, but also for the adults that play a role in children’s education (Kestenbaum, 2005). Piaget also highlighted the role that motivation and emotions play in development. He said that children’s motivations to learn are in great part due to their drive to grow, love and be loved, and assert themselves (Piaget & Inhelder, 1969). Motivation can be achieved by making learning activities relevant to children’s lives and interests as recommended by other pioneers, such as Dewey, Montessori, and Vygotsky (Dewey, 1959; Montessori, 1964; Vygotsky, 1978). Papert went a step further and made a distinction between activities that are relevant to children’s lives and those that children feel passionate about. He believed the latter would be much better at motivating learning (Kestenbaum, 2005). This view highlights the need for providing children with learning opportunities that are flexible or varied enough to help every child find something that speaks to his or her interests. This is an area where computers can prove to be a positive tool due to their flexibility in providing a variety of experiences and learning opportunities. More specifically, researchers have taken into account Piaget’s views on motivation when providing children with technologies that incorporate learning in entertaining ways. Games are increasingly used for teaching a variety of subjects, and are particularly popular in commercial mathematics learning software for children (e.g., Knowledge Adventure, 2014; Zephyr Games, 2013; Learning Company, 2006; Scholastic, 2006). Fisch (2005) provides an overview of basic guidelines to follow when incorporating learning into games. Storytelling is another approach that can make learning more interesting for children. It is often what brings together the games used for learning, but could also be used without a game component (e.g., Cassell, 2004; Hourcade et al., 2004a; Hourcade et al., 2012a). Developmental stages Arguably, Piaget’s best known and most critiqued contribution is his idea of developmental stages. He proposed that all children go through a series of stages in their development on their way to attaining logical, analytical and scientific thinking. At each stage, children present typical behaviors, and are limited in the types of mental operations they conduct. Piaget argued that all children go through the stages in the same order, and none of the stages may be skipped. He proposed age spans for each of the stages but acknowledged that different children go through 10 the stages at different speeds and thus reach stages at different ages (Piaget, 1973; Piaget & Inhelder, 1969). The four stages include the sensory-motor stage (zero - two year olds), the preoperational stage (two - seven year olds), the concrete operations stage (seven - eleven year olds), and the formal operations stage (eleven - sixteen year olds). Piaget’s descriptions of each stage are useful in identifying why children may have difficulty with a particular type of interaction. Different developmental issues can have an impact on the design of technologies, starting with the preoperational stage. Preoperational children (two - seven year olds) are egocentric, meaning they see the world only from their own perspective, and have great difficulty seeing from someone else’s point of view (Piaget, 1995a, 1995b). This can be seen in the difficulty of partnering with children in this age group in the design of technologies (e.g., Guha et al., 2004). Children in the concrete operations stage (seven - eleven year olds) are more likely to appreciate someone else’s perspective, which enables them to better work in teams and as design partners with adults. Preoperational children also tend to concentrate on only one characteristic of an object at a time, a limitation that extends to understanding hierarchies (Piaget 1995a, 1995c). This is one important lesson to remember when designing technologies for this age group: interfaces that require navigation through hierarchies should be avoided and alternatives should be provided. Concrete operational children, on the other hand, are able to understand hierarchies and reverse actions in their head, which can enable them to use a greater variety of technologies and software (Piaget, 1995c). More abstract concepts such as using deductive reasoning and logically analyzing options tend to appear more consistently during the formal operations stage (eleven - sixteen year olds). More details on how children’s problem solving abilities evolve can be found in Appendix A. The idea of developmental stages has been heavily criticized. One of the main criticisms questions the assertion that children will behave consistently on tasks given their developmental stage. Rather, research has indicated that a child’s developmental stage only produces a likelihood that a child will behave in a particular way (Flavell, 1992). Children’s performance in tasks also depends on several factors, such as the amount of information in a task, social support, and instructions. For example, the amount of information in a task can affect performance because larger amounts are more difficult to handle by a limited working memory. Hence children’s working memory capacity can be a confounding variable. Recent research taking these factors into account has provided evidence that children and infants are more competent than Piaget thought, while older children and adults appear to be less competent (Flavell et al., 2002). Another area where Piaget’s developmental stages fall short is in addressing the role that social and cultural factors play in children’s learning and performance in tasks. These issues are explored below under Sociocultural approaches. Similarly, there has been criticism of Piaget’s consideration of logical-analytical thinking as the highest form of intellectual development. Gardner’s multiple intelligences theory proposes that there are other types of intelligences, which is explained under the section on Multiple intelligences in this chapter. Sternberg’s successful intelligence theory takes a practical and inclusive approach in defining intelligence 11 and is described under the Successful intelligence section, also in this chapter. It is still advantageous to know about the typical needs and abilities of children at specific ages, as this knowledge can provide rough guidelines for what may and may not work when designing interactive technologies. Appendix A presents a detailed overview of child development in terms of perception, memory, problem solving, language, and motor skills. Sociocultural approaches The work of Lev Vygotsky, a Russian psychologist who conducted his research early in the 20th century, but whose work did not become widely known until the 1970s, has been quite influential in highlighting the importance of social aspects in child development. Vygotsky thought that language, signs, and tools play a crucial role in cognitive processes. For example, he thought children learn to plan actions by using speech, which later turns into the inner speech of adults. He also saw writing and more generally the use of external tools and signs as ways of augmenting human cognition. As an extension to this, he saw learning as social in nature, observing that children are able to complete tasks with some help from adults Attachment or older children before they can complete Children’s attachment to primary caregivers them on their own. In making this (mostly parents) has a prominent role in the observation, he stressed appropriate view of child development in fields such as social supports as being critical for psychiatry and social work. Attachment is a children’s learning (Vygotsky, 1978). fundamental need for children, rooted in a biological basis. It helps children feel Out of Vygotsky’s ideas come some secure, regulate their emotions, learn to concepts that are often cited in the child- communicate, relate socially, self-reflect, computer interaction and the learning and experience confidence in exploring the sciences literatures. One is the concept of world. Secure attachments occur when scaffolding (Wood et al., 1976), which primary caregivers are consistently refers to the help children require to responsive, emotionally available, and complete a task before they can complete loving. When children do not have secure it on their own. Once children internalize attachments with a primary caregiver, they the process that helps them accomplish a are more likely to show higher levels of task, they are able to complete the hostility and negative interactions with other process individually. Some research on children, less autonomous behavior, low children’s technologies refers to the self-confidence, and poor academic technologies providing the scaffolding, performance (Siegel, 2012). While this book instead of teachers or parents (e.g., focuses on designing technologies for Soloway et al., 1996). When children can children, if we want to help children’s complete a task with scaffolding, but development, especially early in life, we cannot complete it on their own, they are have to consider how technologies for adults in the zone of proximal development affect the level and quality of attention they (Vygotsky, 1978). Vygotsky thought that pay to the children in their care in order to the most appropriate time for children to promote secure attachment. learn is when they are in this zone, rather 12 than when they are ready to complete tasks individually. He also thought that challenging children while providing social supports would help children learn more material more quickly. Many other researchers have followed in the footsteps of Vygotsky, conforming what today are referred to as sociocultural approaches to learning. In these approaches or theories, children’s learning is seen as an active process of interactions with other people and tools; children are not passive recipients of knowledge. Knowledge is not seen as constructed individually in the mind, but socially in the world. These approaches study learning in a given sociocultural context instead of studying individual children in isolation, and study children’s cognition as it connects with society. There are two levels at which the sociocultural context can be studied. One is the overall society and culture to which the child belongs. Researchers have pointed out that in different parts of the world, different kinds of knowledge and skills are valued. Similar claims can be made for different times in history. Thus, cognitive development will always be seen through the lens of a particular sociocultural context. The second level at which sociocultural context can be studied is in the immediate vicinity of the child: how family and school environments provide learning opportunities and scaffolds. Different family and school values will lead children to different routes in cognitive development (Flavell et al., 2002). In many ways, the sociocultural approach to learning goes back to the notion of an apprenticeship, similar to that in middle age guilds, and to what occurs in graduate schools between students and their advisors. One example of more modern sociocultural approaches is situated learning or situativity Literacy Environment theory. This approach sees learning as The family environment can play a occurring in activities where children interact significant role in children’s development. with their environment as well as with adults For example, studies point at higher and other children (Brown et al., 1989; language and cognitive skills for children Chaiklin & Lave, 1993; Greeno, 1998; with access to richer literacy environments. Greeno et al., 1996; Lave & Wenger, 1991). These include literacy activities (e.g., shared Knowledge is not seen as belonging solely book reading), the quality of participation on to individuals, but rather as being distributed the part of primary caregivers (e.g., quantity between them and the tools, artifacts, and and style of speech), and access and other people in their environment. The exposure to appropriate learning materials interactions between individuals and the (e.g., books, toys that enable symbolic play) environment transform both. Thus, these (Rodriguez et al., 2009). Interactive situations are studied rather than the technologies can play a positive role in individuals in them. These theories, as well shaping the family environment, especially as those in similar areas such as social in providing opportunities for shared literacy constructivism, have led to instructional activities and promoting availability of methods where context is seen as an appropriate learning materials. integral part of learning, rather than simply influencing individual cognition (e.g., Cobb & Yackel, 1996; Brown & Campione, 1996). 13 These social approaches and instructional methods appear in contrast to much of the current use of personal computers in education. In the United States, for example, typical use of computers in schools involves children going to a lab where rows of desktop computers are set up, with children often wearing headphones that tether them to their computers. These setups significantly limit the potential for social interactions. On the other hand, more mobile options can facilitate collaborative learning if used appropriately in learning environments (e.g., Hourcade et al. 2008a). Play Play is increasingly considered to have a crucial role in development. There is evidence that it contributes in many physical and cognitive ways, including preventing obesity, and promoting learning and problem-solving skills. The connections to developing social and emotional ties are even more obvious, with play promoting greater social engagement in a pleasant context, enabling children to develop negotiation and self-advocacy skills. Facing challenges as part of play can help children develop resiliency, and can also enable them to “act” in an older, more responsible fashion (Milteer et al., 2012). The challenge for technology design is to enable play with computers to retain the positives of traditional play, including physical activity, rich social interactions, and open-ended possibilities. Computationally and biologically-inspired theories Computationally and biologically inspired theories, such as neuroconstructivism, dynamic state theories, and connectionism, have developed within psychology, building on Piagetian and sociocultural approaches. Their proponents’ goal is to understand how developmental changes occur over time, as opposed to what develops when and under what conditions. To accomplish this goal, these approaches make use of mathematical and computational models. They also attempt to bridge knowledge of the biology of the brain with the higher-level concepts used in traditional cognitive development theories. Finally, because of the use of models, these theories can be tested through empirical studies, where predictions can be made about how developmental change occurs (Mareschal et al., 2007; Schöner, 2009; Oakes et al., 2009). Computationally and biologically inspired theories make a strong emphasis on embodiment, also referred to as situatedness. They see development as occurring through bidirectional interactions between the brain, the body, and the environment (including other people). In particular, the view is that knowledge structures or representations are not independent of the body or the environment, and are only sufficient for a specific context. The problems that prompt developmental changes occur in the body and the environment, and the body and environment are used to solve them. Not only that, but as change occurs, the brain, the body, and the environment change together. The dynamic nature of the environment means that knowledge structures, representations, and behaviors are constantly emerging to respond to changing contexts. These theories have a specific interest in how emergence occurs as a consequence of the interactions between brain, 14 body, and environment. In particular, the theories suggest that cognition and complex forms of behavior emerge in suitable environments. They also suggest that the emergence of skills, behaviors, and so forth is due to diverse processes that unfold over time. These computationally and biologically Embodiment inspired theories also incorporate the The concept of embodiment has seen concepts of plasticity and variability. increased interest in the past decade within Plasticity refers to the ability of nervous the field of child-computer interaction (e.g., systems, including the brain, to dynamically Antle, 2013). This has been brought about change in reaction to experiences and the by an awareness of recent approaches to environment (Anderson et al., 2011). It child development like those described in occurs through changes in neuronal network this section. It has also been prompted by organization. Some of these changes are the greater availability of technologies that directly tied to development, and are thus make it possible for children to interact with more likely to occur during childhood and a computer by using their whole bodies adolescence (Spear, 2013), while those that (e.g., Microsoft Kinect), and to use require the modification of existing neuronal computing devices in a wide variety of networks can occur at any point in human environments (e.g., smartphones). The life (Kolb & Gibb, 2014). concept of embodiment also implies that the context in which technologies are designed The computational models these theories and evaluated is likely to have a significant use are stochastic, meaning that the impact on design and evaluation outcomes. outcomes of a particular combination of brain, body, and environment are not deterministic, but probabilistic. In other words, given the same conditions, the same child may behave differently. This explains within-child variability, which could of course be substantially increased by changes in the environment. As plasticity decreases and knowledge structures and behaviors become more specialized, variability also decreases, with more consistent behaviors likely to be observed. Emergence, Plasticity, and Variability The concepts of emergence, plasticity, and variability have several implications when it comes to designing technologies for children. First is that the use of technologies needs to be studied over time, and while quick sessions may uncover usability issues, only long-term use will help us understand what developmental changes occur when a technology is introduced in a child’s environment. The second is that technologies are likely to have a greater impact on younger children due to their greater plasticity. This means that extra care should be devoted to ensure that the use of technologies has positive developmental effects on young children, especially as ages of first use continue to go down. Finally, to account for variability, any design and evaluation activities should include more children at younger ages (due to greater variability). 15 Siegler and others have identified the issue of high variability in cognitive task performance within as well as between children. They have observed that children will choose from a variety of strategies and will not follow the same strategy consistently as would be suggested by Piaget’s stages of development. For example, in a study asking toddlers to reach for a toy, Chen and Siegler (2000) found that 74 percent used at least three different strategies. Not only that, but children who show greater cognitive variability are likely to fare better in learning (Siegler, 2007). Another cause for variability is that children may take some time before they can apply a strategy to a variety of tasks (Chen & Siegler, 2004). Other theories Privileged-domain theories Privileged-domain theories consider the mind to be domain-specific, with specialized structures that are interconnected. Part of the evidence behind these theories comes from neuroscience and its study of brain activity showing certain parts of the brain to be most often dedicated to certain types of cognitive tasks. In addition, there is evidence that the brain can adapt to uncommon circumstances, reusing parts of the brain for purposes for which they may not typically be used (e.g., deaf children using parts of the brain normally dedicated to auditory processing for visual processing purposes instead). Some theorists also propose that children are born with learning mechanisms tuned to cognitive tasks that are particularly important for humans, such as acquiring language, recognizing faces, perceiving objects, and discriminating between living and non-living things. These mechanisms may explain why children learn very rapidly in some domains (Chen & Siegler, 2004; Flavell et al., 2002). Behaviorism Behaviorism studies learning from the perspective of observing and measuring behaviors as a response to stimuli. It ignores what happens in the brain and treats it as a black box. Skinner (1968) saw learners as operating on the environment and receiving feedback on behavior. Learning a behavior given a set of stimuli is achieved through feedback: positive reinforcement where the learner receives something they want (e.g., a good grade), and negative reinforcement where the learner is rewarded by escaping or avoiding something they do not want (e.g., taking a final exam). Feedback to discourage behaviors and help learners distinguish them from desired behaviors is accomplished through punishment, such as taking away something the learner wants, or giving them something they do not want (e.g., a low grade). Skinner also developed the concept of shaping, whereas a complex task is taught by breaking it up into smaller ones and providing reinforcement for segments of behavior. Behaviorism puts emphasis on drills and practicing where learners remember and respond (Hung, 2001). It can be helpful for situations where automatic responses are useful or necessary, for example, remembering multiplication tables, playing a musical instrument, spelling, and typing. These strategies have been used in educational games. Behaviorism has also been useful in the design of interventions for children with atypical cognitive development, such as children diagnosed with autism spectrum conditions (e.g., Sundberg & Michael, 2001; Venkatesh et al., 2013). 16 Behaviorist approaches can complement approaches that focus on higher cognitive processes by providing the building blocks necessary for completing more complex tasks. With the task of writing, for example, behaviorist approaches can help children develop basic handwriting skills, while constructionist approaches can lead children to collaborative storytelling activities. Problems can occur if behaviorist approaches are used to involve children in higher-level cognitive activities such as storytelling, or if constructionist approaches are used to teach low- level skills such as handwriting. In the latter case though, a combination of both approaches could be advantageous (e.g., getting practice while participating in making something of interest). Skills and intelligence Education systems in many regions of the world, including the United States, are increasingly relying on testing and quantitative measures to demonstrate the educational effectiveness of pedagogical approaches, including the use of technologies. Hence, it is important to be aware of the leading theories of intelligence and how tests attempt to measure intelligence. It is also important to learn about factors that may have a significant effect on academic performance and social wellbeing, such as executive function and emotional intelligence. Psychometric theories Psychometric theories make use of tests to assess and predict the intelligence of individuals, including children. These theories vary in the number of factors believed to influence intelligence. Some like Spearman, proposed one general factor, called (g), while Thurstone proposed seven factors, and Guilford 180 factors (Chen & Siegler, 2004). More recently, Carroll (1993) developed a hierarchical theory with (g) at the top, followed by two strata. The results of numerous studies provide evidence that individual differences in psychometric scores stabilize at about age five or six (Chen & Siegler, 2004). These scores are also good at predicting performance in school. More recent research has found correlations between the performance of infants in tasks such as visual recognition and intelligence quotient (IQ) scores later in life (Chen & Siegler, 2004). IQ tests throughout the last century show a sharp increase in IQ with every generation, to the point where someone who would have scored in the 90th percentile in 1892 would drop to the 5th percentile in 1992. These differences suggest that the environment in which children grow up plays a much more important role than genetics in determining IQ, since genetic mutations explaining these gains could not have occurred in such a short span of time (Sternberg & Kaufman, 1998). Criticism of psychometric theories centers on the difficulty of capturing the richness of intellectual abilities through a few numbers. These theories have also been criticized for failing to take into account social and cultural issues, disregarding some of the factors that people from different cultures consider key to intelligence, and lacking a strong correlation with success in life (Chen & Siegler, 2004; Sternberg & Kaufman, 1998). They also tend to be used as 17 predictors of future performance, and not as a way to prescribe how to best educate children (Gardner & Moran, 2006). Multiple intelligences Gardner and Moran (2006) propose that multiple, somewhat independent, yet interacting intelligences provide a useful way for understanding human cognitive abilities. They propose eight specific intelligences, each with a focus on different types of information: linguistic, logical- mathematical, musical, spatial, bodily kinesthetic, naturalistic (distinguishing between natural and manmade objects), interpersonal, and intrapersonal. Gardner argues that different combinations of intelligences are better matches for different types of professions. For example, he proposed that business people are better suited at having all intelligences at similar strength, while scientists and artists are better suited at having a few intelligences be particularly strong, overshadowing the rest. Gardner’s ideas have inspired educators to make educational activities that teach concepts by introducing them through many entry points, taking advantage of children’s multiple intelligences. Instead of concentrating only on linguistic or logical-mathematical intelligences, as a lot of educational activities do, Gardner’s theory suggests involving additional types of intelligences to introduce concepts. The more entry points into a concept, the more likely a greater number of children will understand it. Kornhaber et al. (2004) discuss ways in which this approach has benefited students. Successful intelligence Sternberg (2003) proposes the concept of successful intelligence as an individual’s ability to succeed in life given the individual’s goals within a sociocultural context. He argues that people achieve success by adapting to, shaping, and selecting environments. This requires people to know about their strengths and weaknesses, and how to compensate for these weaknesses through analytical, creative and practical abilities. These three abilities constitute the three interacting aspects of Sternberg’s triarchic theory. Sternberg and Kaufman (1998) argue that current educational practices overemphasize the use of analytical abilities to the detriment of creative and practical abilities. They propose that educational activities should match students’ strengths in analytical, creative, or practical abilities. Executive function Executive function refers to a collection of processes that are necessary for goal-oriented behavior. These are the processes that are necessary for children to succeed socially and academically. The advantage of focusing on executive function is that it can be improved independently of general intelligence (Blair & Peters Razza, 2007; Bierman et al., 2008). For this reason, executive function processes have been getting an increased amount of attention during the past few years. Anderson (2002) proposes a model of executive function composed of four domains. The first domain is attentional control, which includes selective attention, self-regulation, self-monitoring, 18 and inhibition. Children who are successful in this domain are able to focus appropriately, regulate and monitor their actions to ensure that tasks are completed correctly and in order, and avoid inappropriate actions. The second domain is information processing, which includes efficiency, fluency, and speed of processing. Children who are successful in this domain are able to complete specific tasks quickly and accurately, and are able to quickly react to changes in the environment. The third domain is cognitive flexibility, which includes divided attention, working memory, conceptual transfer, and the use of feedback. Children who are successful in this domain are able to shift attention as needed, learn from mistakes, accept feedback, and are able to develop alternative strategies. The fourth and final domain is goal setting, which includes initiative, conceptual reasoning, planning, and strategic organization. Children who are successful in this domain are able to develop their own set of goals and plan on how to accomplish them in an organized way. Executive dysfunction, on the other hand, is associated with conditions such as attention deficit hyperactivity disorder (ADHD), autism, and dyslexia. In milder forms, it can lead otherwise typically-behaving children to struggle in school. There are empirically validated interventions that can help children struggling with executive skills. Dawson and Guare (2010), for example, provide a widely used guide that includes assessments and interventions, with a primary focus on school applications. There has been evidence that computerized approaches to develop working memory (part of cognitive flexibility) may have a positive impact. In terms of physical activities, there is evidence that aerobic exercise may improve cognitive flexibility and creativity, and martial arts may prove advantageous across a wide dimension of executive function skills. Mindfulness training may also provide advantages, in particular when it comes to shifting attention and monitoring for events. When it comes to curricula used in schools, common strategies used for enhancing executive skills include using socioemotional content, focusing on oral language development, encouraging self-talk, using scaffolds, emphasizing planning by children, and promoting character development including kindness, helpfulness, and empathy (Diamond & Lee, 2011). In spite of the increased attention being paid to executive function skills at individual schools, this is a topic that has largely escaped the attention of government officials, who seem to prefer to focus on standardized tests. By and large, it has also escaped the attention of the child- computer interaction community, even though the topic provides opportunities for engaging children with computer-based interventions that could potentially have a significant positive impact on children. Emotional intelligence Emotional intelligence refers to the ability to reason about emotions, and to use emotions to assist with reasoning. The abilities that have been associated with emotional intelligence include accurately perceiving emotions, using emotions to prioritize thinking and make better decisions (e.g., knowing how to purposefully include or exclude emotions), understanding emotions, and managing emotions (e.g., regulating emotions, reframing situations in a more positive manner) 19

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