How we Learn & Think
All learning is a three part process; first emotion, then reflection, and finally action.
Rudolf Steiner (1921)
Also See: Early Childhood Education
Discipline and Freedom
Ability as a Learnable Resource
HOW THE BRAIN DEVELOPS
Genes and the Environment
Attachment and Relationship Experiences
Brain Trauma Insights
Brain Research and Changing Views of Intelligence
Using Brain Research to Teach through Arts Integration
Make the arts an integral part of the curriculum
Use the power of emotions
Use music to develop math reasoning
Develop a love and command of words early
Create a nonthreatening environment
Give opportunities to move during learning
Provide a synapse stimulating environment
WHAT IS LEARNING AND THINKING?
Learning How to Think
Enhancing Procedural Knowledge
Enhancing Metacognitive Knowledge
Motivational Consequences of Strategy Knowledge
Teaching for Transfer
As Covington, 1998) wrote, “as students struggle to create their own futures two kinds of knowledge are critical: knowing how to learn and knowing how to think.” Learning and thinking are not the same thing, although it is often assumed that if people simply have enough information they will also think effectively. Obviously, this is not necessarily true. We cannot teach facts alone and expect understanding to occur automatically. As Emily Dickinson remarked, “He has the facts, but not the phosphorescence of thought.” Learning and thinking are different because they involve different goals – in the first instance, to recall what is memorable and, in the second, to make meaningful what is remembered. These different goals also involve different mental operations. Learning places a premium on the skills of precise rehearsal and effective recall, whereas thinking demands ﬂexibility, openness, and a spontaneous play of mind (p. 163). Teaching students how to think is important for at least three reasons:
Discipline and Freedom
First, encouraging intrinsic learning goals requires that students have considerable freedom – freedom to set their own learning objectives within reasonable limits and then to decide how best to achieve them. Such freedom requires:
• Monitoring of one’s own progress toward these goals
• The ability to plan
These qualities are rare enough, and they are particularly in short supply among children who see learning as a threat to their sense of worth. For these youngsters, something more is needed than simply providing an opportunity for unlimited rewards (p. 21). Students must also be trained in the skills of intellectual self-discipline that form the essential complement to freedom.
Ability as a Learnable Resource
Second, improving one’s ability to think encourages the will to learn. Learning how to think fosters the view that ability is expandable through experience and practice – the “incremental” view of intelligence (Dweck, 1986, 1990; Dweck & Bempechat, 1983). Students who hold this view tend to tackle more difficult problems, for longer periods of time, and with greater resolve and confidence than do students who hold an ”entity” view of ability. An entity belief presumes that intelligence is a fixed, immutable factor likely of genetic origin that does not yield in effort or improve through the accumulation of knowledge.
Third, instruction in the skills of thinking is also critical to future survival. We can no longer safely assume that what is presently taught in schools will:
• Satisfy future job and civic responsibilities
• Help children adapt to radically different life-styles and to a myriad of other changes that can only be dimly perceived today
The future is overtaking our children at a rapidly accelerating pace. At the center of these changes is the knowledge explosion with its growing glut of facts. Robert Hilliard of the Federal Communications Commission estimates that “at the rate at which knowledge is growing, by the time a child born today graduates from college, the amount of knowledge in the world will be four tunes as great. By the time that child is 50 years old, it will be 32 times as great and 97% of everything known in the world will have been learned since the time he was born.”
Hilliard is serving notice that more information than ever before is needed to remain functional, literate, and adaptive, and that the range and breadth of such knowledge will continue to expand at a staggering pace. Worse yet, information itself is subject to increasing obsolescence at an astonishing rate. As Alvin Tofﬂer (1970) explains, “We are creating and using up ideas and images at a faster and faster pace – knowledge, like people, places, things and organizational forms, is becoming disposable.” Indeed, the half-life of facts today can be measured in terms of months or weeks, even days. (p. 22)
Today schools largely grapple with only the first aspect of the “knowledge explosion” – that of mastering the sheer volume of ever increasing information – by trying to make learning more efficient (sometimes through computer-based instruction) or by requiring students to spend more time at their studies. These solutions are easily recognized as part of the intensification mentality. Merely spending more time will not solve the problem; there will never be enough time. By far the more important challenge is the rapid turnover of information, an issue that has gone largely unaddressed by schools. Clearly, schools must do more than merely dispense facts to be memorized and reproduced later, so-called reproductive thinking (Covington, 1986).
Schools must also instruct in broader, future-oriented skills that include strategic forms of thinking and problem solving. Among other things, being strategic in one’s thinking in the twenty-first century – or in any age, for that matter – means having a keen sense for which information is relevant. As Krates the Elder remarked some twenty centuries ago, “One part of knowledge consists in being ignorant of such things as are not worthy of being known.”
Today as the computer age hits its stride individuals will be confronted more and more with virtually inﬁnite amounts of information, only a fraction of which will be relevant to any given problem. Students must learn to cope with this information glut so that they, and not the machine, will be the master (Covington, 1986).
Fox (2006) tells us, Children follow adults and if adults no longer know what it means to be adult then surely children will not get the message either. If adults lack meaning in their lives, then children will be hard put to ﬁnd it on their own. If adults quit learning, then children will ﬁnd it a greater struggle to be empowered to learn. When I use the word education I am not just talking about children. I am talking about everything adults learn, or think they have learned, and teach others, whether children, young adults, or one another. After all, children return home from school to a house of adults – not only parents or stepparents, but grandparents, uncles, aunts, politicians, journalists, media moguls and personalities, clergy, and makers of ﬁlm, television programs, and commercials.
All adults are involved in education all the time. Children are watching – and learning – or trying to. Nothing is as natural as learning. Learning is to the mind what eating is to the body. It is a daily affair. It can be fun and delightful and delicious. It is also a necessity. Our minds close, our souls dry up, and our hearts shrivel when we are denied learning, just as our bodies shut down when they are denied the necessary nutrients food provides. Rabbi Abraham Heschel says, “Learning is not for life; learning is life.” This means that when we cease to learn we cease to live. To be alive is to be learning. Sad to say, I have met many people – no few in positions of considerable power and responsibility – who long ago ceased to learn. It also means that when we learn we ﬁll up with life. (Fox, 2006)
HOW THE BRAIN DEVELOPS
Because of the dramatic increase in studies of the mind and the brain’s development and deformities, the 1990’s is known to some as the decade of the brain (Siegel, 2012). Many of those studies have now been completed and new information about how the brain and mind are developed and traumatized is now available. In updating his book The Developing Mind (2012) Daniel Siegel M. D. and his researchers at UCLA read over 2,000 papers on those studies covering a twelve year period since his first edition was published in 1999. There is now more current information about the brain than ever before.
As Siegel’s (2012) research tells us, the brain is a complex system of interconnected parts that functions as an integrating system of subsystems that intertwines the functions of the brain and body. The activation of neural pathways directly influences how connections are made within the brain and how the regulation of genes is altered. Experience shapes the activity of the brain and the strength of neuronal connections throughout life. The brain is also dynamic in that it is continually in a state of change. “Cortical plasticity” is the process by which the brain shapes itself in response to various environmental stimuli (p. 22). New findings on the study of neuroplasticity reveal that the brain is open to further development throughout the lifespan. (Doidge, 2007)
The brain has an estimated one hundred billion neurons with each neuron having an average of ten thousand connections (synapse) that directly link itself to other neurons. There are thought to be about one million billion of these connections making it the most complex structure, natural or artificial, on earth (Green, 1998). The vast numbers of neural connections are not static as the brain continually changes its synaptic interconnections in response to experience (Doidge, 2007) (p. 15)
The neurons communicate with one another through a combination of electric and chemical impulses and because of the spider-web-like interconnections, the number of “on-off” patterns of neuronal firings is immense, estimated at ten times ten million one million times. The growth of myelin along the lengths of neurons increases the speed of nerve conduction by one hundred times and reduces the refractory period during which a just-fired neuron must rest before firing again by thirty times. Thus myelin functionally enhances the linkage among synaptically connected nerve cells by three thousand times (p. 23). This is an example of electrochemical energy flow. Because of this huge capacity and possibility of an immense variety of activity, no man made computer can come close to the organization and functionality of the human brain.
The brain is divided into two hemispheres, the right and the left. The left side is thought to be the “verbal” domain where activities such as language and arithmetic calculations take place and helps us listen carefully, be logical and stay calm (Karp, 2008). The right side of the brain controls many of our “non-verbal” functions including visual-spatial activities like reading a map and the more “imaginative” and “artistic” activities. The right half controls the rapid responses to the nervous system by making quick decisions and providing instant face recognition. Unlike the thoughtful left side, the right side is distractible, impulsive, and emotional. Some of these activities are interchangeable and can be performed by either side of the brain as in the case of people that are born where only one side of their brain has developed (Doidge, 2007).
The cerebellum, which means “little brain,” is found at the back of the brain underneath the two hemispheres. The cerebellum is responsible for the body’s balance and coordination which controls actions such as writing, walking, throwing a ball and speaking. At birth, the cerebellum is small which accounts for the lack of balance and coordination in infants but as the child grows so does the cerebellum and by the end of the first year the child can stand, reach and grab items, and contort the mouth muscles to make sounds (Karp, 2008).
The “lower structures” of the brain contain the circuits that regulate energy flow such as states of arousal, alertness, body temperature, respiration, heart rate and the survival reactions of fight-flight-freeze. The lower brain structure also contains the hypothalamus and pituitary which are responsible for body equilibrium, hormonal release and can be adversely affected by stress and trauma (p. 16).
The centrally located limbic region contain a cluster of neurons called the hippocampus that control emotions, motivation, goal-directed behavior, nitration of memory and the attachment system that enables young mammals to depend upon their parents for safety and security. This region also permits the integration of such mental activity as the appraisal of meaning, the processing of social signals, the activation of emotions and memory in the recall of facts, and the autobiographical details of an on-going experience. Included in this region is the cerebellum which links body motion, mental states and cognitive processing (p. 18).
The top of the brainstem is the thalamus which serves as a gateway for incoming sensory information and the mediation of conscious experience. The “higher structures,” such as the cerebral cortex, mediate “more complex” information processing functions such as perception, thinking and reasoning. These frontal neocortical areas are considered to be the most evolutionary “advanced” in humans and mediate the complex perceptional and abstract representations that make up our thought processes (p. 17).
The cortex matures from back to front with the frontal regions continuing active growth well into young adulthood. The prefrontal cortex is thought to play a major role in working memory (for example, where you left your keys) and the focusing of conscious attention. This region also links the perception of communication signals from other people creating a wide spectrum of integration from body functions to social awareness which includes self-awareness, empathy, emotion regulation and attachment (p. 18).
Prefrontal cortex of our brains is instrumental in managing what is called “executive function” which is our capacity for impulse regulation and attentional control; cognitive flexibility; task prioritization; organize plans and goal setting; and complex information processing (Anderson, 2002) (p. 42) Other research suggested that the prefrontal cortex of aggressive children actually haven’t developed, or are developing more slowly, so that they simply do not yet have brains capable of helping them regulate their behavior. But brains are changeable in that learning and repeated experience can actually alter the physical structure of the brain, creating new neuronal pathways as memory that may be stored in the synapses of our nervous system. (Green, R., 2012)
Self-regulation appears to depend upon neural integration. Relationships stimulate the growth of integrative fibers in the brain, whereas neglectful and abusive relationships specifically inhibit the healthy growth of neural integration in the young child (Teicher, 2010). Even impairments to health that are not experientially derived, such as autism, bipolar disorder, and schizophrenia, have now been shown to reveal impairments to neural integration (Zhang, 2010). Interpersonal experiences continue to influence how our minds function throughout life, but the major structures – especially those that are responsible for self-regulation – are initially formed in the early years. Impairments to self-regulation, held by the field of developmental psychopathology as central to mental dysfunction, may be fundamentally impairments to self-organization (p. 28).
Genes and the Environment
In an era when science is enabling us to understand human experience in new ways, it is important to examine the common debate about how much of development and personality can be attributed to “nature” or genetics, as opposed to “nurture” or experience. Brain development is a product of the effects of experience on the unfolding of genetic potential. Genes encode the information for how neurons are to grow, make connections with each other, and die back as the brain attains differentiation of its circuitry. These processes are genetically preprogrammed and experience-dependent (p. 30).
An infant is born with a genetically programmed excess in neurons, and the postnatal establishment of synaptic connections is determined by both genes and experience. Genes contain the information for the general organization of the brain’s structure, but experience determines which genes become expressed, how, and when. The expression of genes leads to the production of proteins that enable neuronal growth and the formation of new synapses. For the growing brain of a young child, the social world supplies the most important experiences inﬂuencing the expression of genes, which determines how neurons connect to one another in creating the neuronal pathways which give rise to mental activity (p. 32).
Genes have two major functions in that they act as “templates” for the information that is going to be passed on to the next generation and they have a “transcription” function that determines when, which and how proteins will get synthesized and thus expressed. Transcription is directly affected by experience in that it alters the mechanisms that regulate gene expression which is called “epigenesis.” In epigenesis, the sequence of DNA in a chromosome does not change, but the molecules that control gene expression do. Early in life, interpersonal relationships are a primary source of the experience that shapes how genes express themselves within the brain. Changes in epigenetic regulation of gene expression induced by experience can be long-lasting and may even be passed on to the next generation by way of the alterations of epigenetic regulatory molecules in the sperm or egg (Meaney, 2010).
More common, everyday experiences shape brain structure. The brain’s development is an “experience-dependent” process, in which experience activates certain pathways in the brain, strengthening existing connections and creating new ones. Development is also in part “experience-expectant,” in that genes instruct specific circuits to be created but that maintenance of those synaptic linkages requires stimulation from the specie’s general experiences. Lack of experience for these circuits can lead to the diminution of synaptic connections and cell death in a process called “apoptosis,” “parcellation” or “pruning.” This is sometimes called a “use-it-or-lose-it” principle of brain development. Whether experience-expectant or experience-dependent development is occurring, synaptic connections are maintained by ongoing neural firing that is created with experience (p. 22).
In experimental animals, enriched environments have been shown to lead to increased density of synaptic connections and especially to an increased number of neurons and actual volume of the hippocampus, a region important for learning and memory (Hockfield, et al, 1998). “Heredity plays a highly important role in the form of these different (behavioral) repertoires, but there is now clear evidence that the environment can play a role in shaping brain structure and, in turn, learning behavior (Diamond, 1988).
Experiences lead to an increased activity of neurons, which enhances the creation of new synaptic connections. This experience-dependent brain growth and differentiation is thus referred to as an “activity-dependent” process. It is for this reason that the early years of life are closely looked at to understand the ways in which the mind develops and how Interpersonal experiences continue to influence our minds function throughout life, however the major structures, especially those that are responsible for self-regulation, appear to be formed in the early years (p. 24).
Genes do not act in isolation from experience. Genes and experience interact in such a way that certain biological tendencies can create characteristic experiences. For example, certain temperaments may produce characteristic parental responses. The question isn’t “Is it heredity or experience?”, but “How do heredity and experience interact in the development of an individual?” Recursive repetition, what an individual’s mind presents to the world, can reinforce the very things that are presented. A typical environmental/parental response to a child’s behavioral output may reinforce that behavior. Therefore, the child plays a part in shaping the experiences to which the child’s mind adapts (p. 31).
Behavior itself alters genetic expression, which then creates behavior. In the end, changes in the organization of brain function, emotional regulation, and long-term memory are coordinated by alterations in neural structure. Experience, gene expression, mental activity, behavior, and continued interactions with the environment (experience) are tightly linked in a transactional set of processes. Thus, as in the way in which nature and nurture, genes and experience are inextricably part of the same process (Meaney, 2010).
Genetic studies of behavior commonly note that fifty percent of personality features is attributable to heredity. The majority of the other half of the variability is thought to be due to “non-shared” aspects of the environment, such as school experiences and peer relationships (Triandis, et al, 2002).
Each individual’s history reﬂects an inseparable blend of how the environment, random events, and the person’s temperament all contribute to the creation of experiences in which adaptation and learning recursively shape the development of the mind. Gender-based differences in brain development, in conjunction with cultural profiles, may be a factor in moving development in a certain direction that reinforces itself across a lifespan, (Eliot, 2010) however there is far more in common across the genders than there are neutral differences (p. 32). Also, the complicated interaction of genes, experience, and epigenetic regulation is also revealed in the inheritance patterns of certain psychiatric disorders, such as schizophrenia (Isles & Wilkinson, 2008).
Attachment and Relationship Experiences
An infant who has a healthy, secure attachment has had the repeated experience of nurturing, perceptive, sensitive, and predictable caregiving responses from her mother, which have been encoded implicitly in her brain. She has developed a generalized representation of that relationship with her caregiver – a mental model of attachment – which helps her know what to expect from her mother. Given that these repeated experiences have been predictable, and that when there have been disruptions in mother-infant communication the mother has been relatively quick and effective at repairing the ruptures, this fortunate infant has been able to develop a secure, organized mental model of their emotional relationship. Her implicit memory anticipates that the future will continue to provide such contingent communication. When the child’s mind has been seen clearly and responded to with affection and compassion, the implicit self of the child develops well (p. 54).
An infant with an insecure attachment may have experienced his parents as less predictable, emotionally distant, or perhaps even frightening. These experiences, too, become encoded implicitly, and the infant’s mind has a generalized representation of this relationship that can be filled with uncertainty, distance, or fear. Being alone with a parent who has been the source of confusion and terror can reactivate these implicit representations and create a very unpleasant, disorganizing, and frightening internal world for the infant. This state of mind, a part of his emotional memory, is implicitly learned during the first year of his life. These implicit memory encodings are more than simply recollections; they shape the growing child’s architecture of the self. This is the heart of implicit memory (p. 54).
By a child’s first birthday, these repeated patterns of implicit learning are deeply encoded in the brain. Indeed, attachment studies at this time yield striking differences in infants’ behavior when they are with each parent. An infant’s states of mind when she is with the mother can affect her differently from those that are activated when she is with her father. This is the origin of the differences that can be seen in the infant’s attachment to the two parents. By eighteen months, the maturation of various parts of the child’s brain has allowed for the blossoming of her comprehension and expression of language. At about this time, frontal parts of the brain are developing rapidly and enable her to have evocative memory, in which it is believed she is able to bring forward in her mind a sensory image of a parent in order to help soothe herself and regulate her emotional state (Fonagy, et al, 2007). Infants are likely to be calmed by the image of a parent with whom they have a secure attachment, and to be anxious, distant, or fearful with a parent with whom they have an insecure attachment (p. 55).
Relationship experiences have a dominant influence on the brain because the circuits responsible for social perception are the same as or tightly linked to those that integrate the important functions controlling the creation of meaning, the regulation of bodily states, the modulation of emotion, the organization of memory, and the capacity for interpersonal communication. Interpersonal experience thus plays a special organizing role in determining the development of brain structure early in life and the ongoing emergence of brain function throughout the lifespan (p. 33).
Attachment is based on collaborative communication. Secure attachment involves contingent communication, in which the signals of one person are directly responded to by the other. But why is this type of reciprocal communication so important? Why doesn’t it happen in all families? During early development, a parent and child “tune in” to each other’s feelings and intentions in a dance of connection that establishes the earliest form of communication. Early studies suggest that healthy, secure attachment requires that the caregiver have the capacity to perceive and respond to the child’s mental state (Ainsworth, 1991).
It is these remembered early reciprocal communication experiences that allow a child’s brain to develop a balanced capacity to regulate emotions, to feel connected to other people, to establish an autobiographical story, and to move out into the world with a sense of vitality. The capacity to reﬂect on mental states, both of the self and of others, emerges from within attachment relationships that foster such processes (Tronick, 2007).
Siegel (2012) calls this capacity “mindsight” – the ability to see the internal world of self and others. It may be essential in healthy relationships of many kinds. Mindsight permits integrative communication in which individuals are honored for their differences and compassionate connections are cultivated that link one mind to another. The integrative function of the brain is what permits flexible and adaptive neural regulation, and so interpersonal relationships that are integrative promote healthy self-regulation (p. 34).
These patterns of communication literally shape the structure of the child’s developing brain. These important early interpersonal experiences are encoded within various forms of memory but the need for this type of communication and connection may not end with childhood. As adults, we need not only to be understood and cared about, but to have another individual simultaneously experience a state of mind similar to our own. With this shared, collaborative experience, life can be filled with an integrating sense of connection and meaning (p. 35).
Children who have had no experience with an attachment figure (not merely suboptimal attachment, but a lack of attachment) for the first several years of life may suffer a significant loss of the capacity to establish intimate interpersonal relationships later on (Bowlby, 1988b). Even the ability to perceive the mental side of life may require interactions with caregivers in order to develop properly (Schick, et al, 2007).
Brain Trauma Insights
Early childhood brain trauma include physical blunt force, audio, electromagnetic, fright, air pollutants, malnutrition, toxins, drugs, and oxygen deprivation. The long lasting effects early childhood trauma are dependent on the duration of a specific trauma and subsequent treatment (Teicher, 2010). As we have seen, the brain is constructed by genetics, by aspects of the physiological internal environment (such as nutrients, hormones, toxins, drugs, or lack of oxygen), and by experience (p. 54). What’s interesting is that digital technology is fundamentally reliant on the flow of electricity which is exactly what the human body uses to function both physically and mentally.
Understanding how trauma affects the developing brain can yield insights into the subsequent impairments in memory processing and the ability to cope with stress (p. 196). For example, traumatic experiences at the beginning of life may have profound effects on the integrative structures of the brain, which are responsible for basic regulatory capacities and enable the mind to respond later to stress (Teicher, 2010).
In vitro factors such as infections and exposure to toxins can influence the early development of the nervous system in ways that are not dependent upon the genes themselves. Genetic variables may influence vulnerability to a condition such as schizophrenia, but they may require exposure to such an agent for disease to be induced. Studies of individuals with certain atypical neurotransmitter variants, called “alleles,” reveal observable differences in those individuals only when they are exposed to a severe developmental challenge such as abuse early in life (Caspi, et al, 2003).
Those with the atypical variants do extremely poorly in their lives, whereas those with the typical variants are less severely affected. Without the experience of the abuse, the individuals may have no phenotypic differences discernible to an observer. The epigenetic (external factors that affect how cells read genes) regulation of gene expression may vary even in individuals who share the same genes (p. 32)
Adolescence is a period of intense pruning of the nervous system, and vulnerable brains may be especially at risk following this period of development. This parcellation, also called pruning or “apoptosis,” can unmask latent vulnerabilities. The timing of this parcellation process can help us explain the unfolding of serious psychiatric disturbances during and immediately following adolescence. For these reasons how the child’s environment offers support or intensifies stress can directly influence the occurrence and progression of psychiatric illness. Children who are exposed to significant trauma early in life, for example, have epigenetic changes that make the HPA axis less adaptive in ways that appear to last a lifetime (McGowan, 2009). Future studies will need to investigate whether clinical interventions with such individuals may be able to reverse these structural and epigenetic impacts of trauma on the developing brain (p. 32).
The neural activity of the functioning of the mind alters the physiological environment of the brain, and thus itself can produce changes in gene expression. This can be seen in the production of corticosteroids as a response to stress, which directly influences gene function. In children with shy temperaments, for example, there is a huge physiological response to even mild environmental changes. Such children create their own internal world of stress responses that heighten their brain’s reactivity to novelty (Gross, 2002). Likewise, a child traumatized early in life will have an alteration in physiological response, such that small stressors lead to large hormonal responses. Thus both constitutional and experientially “acquired” reactivity can lead to further physiological features that maintain the hypervigilant response over time (McGowan, 2009).
Because of this, we see that abused children have abnormal responses of their stress hormone levels, which are in part due to changes in the regulation of the genes in these areas of the brain responsible for reacting to stress (McGowan, 2009). Hydrocortisone in sustained and elevated levels can become toxic to the brain (DeBellis, 2005). As we have seen, early experience shapes the regulation of synaptic growth and survival, the regulation of response to stress, and even the regulation of gene expression. Experience directly shapes regulation (p. 22).
Studies are now beginning to reveal the important ways in which we may have embedded in our own nuclear material the ways in which our parents and even our grandparents experienced stress, had alterations in their epigenetic control mechanisms, and then passed these changes on to us via the gametes from which we were formed (Szyf, et al, 2010). There are profound implications of these new findings for our understanding of development and the emergence of patterns of growth, temperament and other inborn qualities of nervous system functioning, and the intergenerational transmission of stress and trauma (p. 24).
Recent studies in trauma (Teicher, 2010) and in neural functioning in the non-task-performing default mode or “resting state” (Zhang & Raichle, 2010) support this proposal that impaired integration is the common mechanism among disorders of health, whether they have primarily experiential or non-experiential (e.g., genetic, toxic, infectious, or random) origins.
Jerome Kagan has demonstrated that parenting behavior makes a large difference for the trajectory of development. In their research, those parents who supportively encouraged their shy children to explore new situations enabled the children to develop more outgoing behaviors than those parents who did not help their children with their fears. These and other intervention studies clearly demonstrate that parenting has a direct effect on developmental outcome, even in the face of significant inherited features of physiological reactivity (Kagan & Fox, 2006).
Brain Research and Changing Views of Intelligence
Cornett (1999) reports that new views in brain research consider cultural, social, and environmental factors that raise or lower intellectual capabilities – factors that include signiﬁcant arts experiences, such as learning to play musical instruments. Pioneering brain research, like T. Berry Brazelton’s, supports this perspective. Hidden links between brain activity and how the brain comes to be structured are now made visible through microscopic analyses of children’s brains (autopsies, PET scans, and MRIs). Studies during childhood show that the brain actually grows like a budding and branching tree, depending on which areas are “sparked.” As mentioned, by adulthood the connections in the brain number more than 100 trillion (p. 11).
Music is heard and a link is forged, beautiful colors and shapes surround a child and connections are made, a baby is rocked or cuddled and another circuit is wired. The key is not exposure, but a pattern of repeated stimuli that sculpt the brain. As Nash (1997) points out, “Deprived of a stimulating environment, a child’s brain suffers . . . children who don’t play much or are rarely touched develop brains 20% to 30% smaller than normal” (p. 51). Windows of opportunity to develop particular abilities begin to close as early as age 10 as a “pruning” of excess brain synapses starts (Nash, p. 50). The window for human visual acuity development only lasts until about age 8; we cannot ignore the power of the environment to form neural connections. Use them or you lose them.
What we eventually do and become depends on how each of the brain’s billions of neurons link to thousands of other neurons (p. 12). Each child’s brain can form quadrillions of connections, but the number and strength depend on the transformative power of repeated experience. “Each time a baby tries to touch a tantalizing object or gazes intently at a face or listens to a lullaby, tiny bursts of electricity shoot through the brain, knitting neurons into circuits as well deﬁned as those etched onto silicon chips . . . when the brain does not receive the right information – or shuts it out – the result can be devastating” (Nash, p. 54). Emotionally deprived babies develop “sad brains” when the center for joy and happiness (left frontal lobe) does not receive stimulation to “get on line” (p. 12).
Using Brain Research to Teach through Arts Integration (see: Innovative Methodologies – Teaching and Learning through Art Integration)
Good teachers know that lecturing on the American Revolution is far less effective than acting out a battle.
Robert Sylwester, University of Oregon
1. Make the arts an integral part of the elementary curriculum.
Many windows of the mind close before we are out of elementary school. If schools were structured on brain research, there would be daily music and movement. Student passivity during lectures would be replaced with hands-on art and drama activities.
2. Use the power of emotions to release memory proteins.
Engage students in experiences that call for feelings to be felt and expressed. For example, literature and art discussions, hands-on art making, working with background music, dance and creative movement all trigger emotional as well as intellectual responses. Dramatic play and exploration of art materials have the potential to alter brain chemistry, creating a feeling of optimism and well-being because play taps into brain chemicals involved in pleasure: dopamine causes elation and excitement, and endorphin and norepinephrine heighten attention (Brownlee, 1997).
3. Use music to develop math reasoning.
The window for prime development of the brain area for music is from three to ten years of age, and exposing children to music rewires neural circuits (research at University of Konstanz in Germany): “the amount of somatosensory cortex dedicated to the thumb and ﬁfth ﬁnger of the left hand was signiﬁcantly larger than in non-players [string instrument players]” (Begley, 1996, p. 57). The younger the child was when she or he took up an instrument the more the cortex was developed. There is evidence that these circuits endure for life; consider those who successfully return to an instrument later in life after childhood exposure (Begley citing work of Shaw at the University of California-Irvine). What’s more, the circuits for math reside in the brain near those for music, possibly accounting for the correlations between music exposure and math performance.
Preschoolers who received music instruction for eight months scored 34 percent higher in spatial-temporal ability than other preschoolers. (They were tested with mazes, patterns and geometric ﬁgures) (Rauscher et al., 1997). One author concluded that “when children exercise cortical neurons by listening to classical music, they are also strengthening circuits used for mathematics.” He believes the “Mozart Effect” may be a result of exciting “inherent brain patterns [used] in complex reasoning tasks” (Begley, p. 57).
4. Develop a love and command of words early.
It is now clear that children are capable at younger ages to use language, music, art, movement, and drama to make meaning; the optimum learning “window” is ten years, beginning at birth. We should tap into these capacities and not teach down to children. Instead of back to the basics, we need to move forward to a future rich in arts-based learning, including daily poetry sharing, reading aloud, singing, story-telling, and dramatic conversations to stimulate growth in the auditory cortex.
5. Create a nonthreatening environment.
Stress and threats cause the brain’s amygdala to ﬂood the brain with chemicals potentially harmful to development of the cortex, which causes problems with understanding. The arts have the power to relax and calm; for example, certain background music can give tranquility.
6. Give opportunities to move during learning.
Restricted physical activity inhibits brain and development (Begley, 1996, p. 61). For example, a child in a body cast until age 4 never learns to walk smoothly. Drama and dance are possible avenues to allow students to learn kinesthetically – to use movement essential to development.
7. Provide a synapse stimulating environment.
This implication is from research on animals raised with playmates, toys, and hands-on stimuli. Privileged rats grew 25 percent more synapses than rats deprived of stimuli. Since the brain is a malleable mass with inﬁnite potential, teachers and parents need to do what’s necessary for children to be all they can be. Childhood experiences stimulate “which neurons are used, that wire the circuits of the brain as surely as a programmer at a keyboard reconﬁgures the (p. 13) circuits in a computer. Which keys are typed – which experiences a child has – determines whether the child grows up intelligent or dull, fearful or self-assured, articulate or tongue-tied” (Begley, 1996, p. 56).
WHAT IS LEARNING AND THINKING?
In Covington (1998) according to Phye & Andre (1986) thinking is the mental operations involved in dealing with problems, however most psychologists think of mental operations in terms of different kinds of knowledge arranged in the top-down structure of (p. 169) Metacognitive knowledge; Procedural knowledge; and Content knowledge (Covington, 1998).
Content Knowledge is the basic requirement for all thinking as in access to information. Also known as “declarative” content knowledge includes dozens, perhaps hundreds, even thousands of facts, figures, and other data arranged in charts graphs. Facts are the basic ingredient of all problem solving. They are not thinking, but thinking is not possible without them.
Procedural Knowledge is the repertoire of mental “procedures” needed to make sense of facts. Procedural knowledge represents the how of problem solving such as the rules of a game or how a banking system works. Typically, procedural knowledge relates closely to the content of the problem itself, so close in fact that sometimes procedural and content knowledge literally fuse. Procedural knowledge can also transcend a given subject matter and apply broadly to most problems and disciplines. This is the realm of knowing how to think of ideas or how to look at old problems in new ways. Knowing how to evaluate ideas in light of new information is also part of procedural knowledge (p. 170).
Metacognitive Knowledge is the overall executive function of the integration of all prior sources of knowledge. Successful thinkers view problem solving in its entirety, not just as an assortment of isolated subroutines, disconnected facts, or disembodied skills. Nowhere is the statement “the whole is greater than the sum of its parts” more apt than when applied to problem solving. Good thinking is more than simply the sum total of all procedural and content knowledge. And there is the corollary that good thinking does not depend solely on the size of one’s content and procedural knowledge base. It is what one does with one’s knowledge that counts most as in how information is selected, arranged, and prioritized. The essence of metacognitive knowledge is, embodied in Albert Camus’s celebrated quip, “An intellectual is someone whose mind watches itself” (p. 171).
A key aspect of metacognitive knowledge involves knowing how to create plans of action and monitor them (Friedman, Scholnick, & Cocking, 1986). The parallel between planful thinking and a military campaign is near perfect. Successful generals arrange. Their troops (cognitions) in a marching order that is best suited for some overall purpose, whether it be to defeat the enemy or to withdraw gracefully to fight another day. These moves and countermoves are controlled by broad plans of action, which in the case of potentially less violent pursuits, such as plotting one’s next move at the negotiating table or on the playing field, involve checking the results of that move and then revising one’s strategies accordingly.
Broad planning strategies have wide application by analogy. For example, like chess masters who must “protect the center of the (p. 171) board,” politicians must protect their ﬂanks, and television evangelists must control their revenue base among the elderly and gullible by at least appearing to be respectable and pious. And even the youngest of problem solvers have their survival strategies, a fact appreciated by all parents who have been victimized by the “divide (mom and dad) and conquer” ruse.
Sometimes these plans of action are best conceived of as a series of abstract steps or mental operations that must be properly sequenced. From this angle effective problem solving involves deciding at a given point in one’s work whether, for instance, it is more fruitful to suspend judgment and give free rein to speculation in search of entirely new ideas, or whether, on balance, it would be best to proceed by evaluating the ideas one already has. This balancing act implies appreciating when one is on the right track or, conversely, recognizing the danger of being overwhelmed by too much information and, once having realized the danger, knowing what to do about it (Gick & Holyoak, 1983; Mayer, 1989). Fortunately, there is evidence that individuals can be taught to create and use analogies as a problem-solving tool.
By transforming the unfamiliar and overwhelming into the familiar and understandable reduces cognitive overload and promote better thinking. The ability to grasp the essential elements of a complex situation is the benchmark of effective thinking. As Nietzsche said, “He is a thinker – that means he knows how to make things simpler than they really are” (p. 173).
The educational significance of the top-down knowledge model is reﬂected in a growing awareness that thinking, far from being a passive activity, is an active, constructive attempt by the learner to create meaning. Above all, this process involves the capacity to think about thinking and the purposeful arrangement, assembly, and orchestration of different kinds of knowledge to achieve a larger goal (Sadoski & Paivio, 1995). Given all the complexities involved, and the many forms that problems can take, it is a wonder that humans think at all. At every level of the knowledge hierarchy there is evidence of massive deficits in thinking (e.g., Oka & Paris, 1987; Sowder, 1987).
In education students should be taught to see the larger utility of what they are learning in school. Students are typically unable to recognize that what they are studying in one subject-matter area relates to other areas (Bailin, 1987), nor do they appreciate the relationship between what they are learning now and what they hope to accomplish in the future (Stake & Easley, 1978). When students are driven to outperform others, they retreat to low-level thinking strategies that favor rote memorizing (Nolen, 1987, 1988). Anxiety degrades intellectual functioning to the point that many students operate at an almost witless level of existence. Very little time is actually devoted to teaching thinking – at least thinking in the active sense. All too often students believe that the reason for studying mathematics is to get the right answers, not to improve their quantitative-thinking skills; likewise, they believe the purpose of studying history is to memorize names, dates, and places; and the reason for writing compositions is because one must! (p.174)
The goals of content mastery need not proceed in a mindless fashion. From a larger perspective learning facts is best conceived of as a process of assimilating new information to be fitted meaningfully into the child’s conceptual world and, in turn, to stimulate the expansion of that world. As William James remarked: “The art of remembering is the art of thinking. . . . Our conscious efforts should not be so much to impress or retain (knowledge) as to connect it with something already there.”
Learning How to Think
Regarding the effort to teach students to think the best evidence comes from studies conducted in schools using instruction of sufficient scope to qualify as general mental skill training, and with enough evidence gathered on their effectiveness to permit reliable conclusions. The Productive Thinking Program’s (Covington, Crutchfield, Davies, & Olton, 1974) emphasis is on the training of metacognitive and planning mechanisms and is a course in learning to think designed for upper elementary school children (p. 177). Whenever students got stuck on a problem, they are directed to consult thinking guides. In this way students are encouraged to review problems periodically to consider whether the task has changed, to judge what has been accomplished so far, and then to decide what additional facts or next steps are needed to move closer to a solution.
Cognitive skill instruction is reinforced through the use of identification models. A storyline is developed around two school-age children (Jim and Lila, brother and sister). Students work on a problem in tandem with Jim and Lila – first students producing their own ideas, then Jim and Lila responding with theirs (feedback). The models are not meant to be perfect; they are depicted as making mistakes but also learning from them, and gradually improving, with the result that they become more self-confident.
Enhancing Procedural Knowledge
The results of a number of studies using the Productive Thinking Program suggest that systematic instruction improves the procedural skills associated with problem solving. For example, after instruction students generated more ideas and of higher quality compared with the idea production of a group of matched control students who had no mental skill training. Instructed students also demonstrated an improved ability to ask questions, especially when it came to strategic inquiries that helped them to identify the nature of the problem.
The number of actual problem solutions also increased after instruction. In one study (Olton & Crutchfield, 1969) students were challenged to think of ways to kill a malignant tumor deep inside the human body using X-rays but without harming the surrounding healthy tissue. Instructed students discovered solutions at a rate (p. 179) twice that of control children. The fact that this particular problem was administered four months after training attests to the longevity of the instructional effects. Also of significance is the fact that these thinking gains occurred on a problem that was quite different in content from those used for practice.
Enhancing Metacognitive Knowledge
What are the prospects for fostering the metacognitive, managerial aspects of problem solving? In one study employing the Productive Thinking Program (Olton et al., 1967), students were given an unfamiliar problem and asked to select the best planning steps from a list of alternative actions as the problem unfolded. Each set of decision-making options differed in appropriateness depending on previous events, but they always included a “best” decision; a “second best” decision (reasonable, but not as good as the first); a “contrary fact” decision (one that ignored an already established fact); (p. 180) an appealing but irrelevant decision; and finally, a decision that would bring the problem to a premature closure. Instructed students were better able than control students to track the most effective course of action throughout the entire problem-solving sequence and in the process were less attracted to “appealing but irrelevant” actions, and less likely to be seduced by “contrary” actions.
Most school tasks involve elements of strategic planning. For example, writing essays consists largely of iterative cycles of planning, drafting, and revising, and, when necessary, redrafting the entire composition as the student strives to create a more satisfying product. Likewise, reading for comprehension usually involves a process of successive cycling as well (Anderson, 1995; Paris, Lipson, & Wixson, 1995): looking ahead to anticipate, looking back to check and test one’s recall, summarizing what is important so far, and filtering new information through the lens of prior understanding. Also, at its most effective, study for a test is also an exercise in strategic planning. Knowledgeable students seek out information about the upcoming test to determine the kinds of demands it will place on them, by inquiring, variously: “What must I remember?” “Must I remember it again later?” “What kind of test?” “What aspects (p. 181) of the assignment will be most emphasized?” (Bransford, Nitsch, & Franks, 1977)
The fact that students can be taught to plan better takes on considerable importance in light of speculation that links intelligence to the ability to plan (Sternberg, 1985). It has been proposed that intelligence, in actuality, represents the ability to think strategically, that is, the capacity to plan for and make the most of one’s personal resources as situations change (Borkowski, Johnston, & Reid, 1985; Derry & Murphy, 1986).
These findings are likely what Alfred Binet, (1909) the father of the mental test movement, had in mind almost a century ago when he observed that ”One increases that which constitutes the intelligence of the school child, namely the capacity to learn and improve with instruction” (pp. 54-55). Binet would almost certainly have embraced the concept of “working intelligence” (Scribner, 1984). In school, working intelligence means:
• Being able to recognize when one does not understand a concept,
• Knowing how to make a difficult assignment easier, and
• Knowing what to do when previously successful learning strategies are no longer effective
All these actions can be trained, and it is in this sense that we say ability can be modified and improved. A more contemporary interpretation of Binet’s position was offered by Terry McNabb (1987) when she also proposed that ability implies strategy, in that those students who (p. 182) possess larger arsenals of thinking strategies are better able to solve problems. Thinking strategies as a concept, then, suggest a more ﬂuid type of ability – more of a resource than a fixed capacity.
Motivational Consequences of Strategy Knowledge
Does strategy instruction increase the willingness of students to think in more deeply about problems? The prospects are encouraging for the fact that the notion of strategic planning bridges both cognitive and motivational domains in several ways. Strategy knowledge increases beliefs that ability is an incremental process. We know that such incremental beliefs about ability are associated with an increased willingness to tackle more difficult problems, for longer periods, and with greater resolve and confidence (Dweck & Goetz, 1988).
A study by McNabb (1987) confirms this point. A series of mathematics problems was administered to two groups of upper elementary students. One group received strategy-related messages (“To solve problems like these, you have to use good methods”). The other group was given effort-related messages (”To solve problems like these, you will have to try harder”). Although both groups received the same procedural training (p. 183) only the strategy group consistently employed these procedures and, as a result, performed better on a final achievement test. Moreover, when computational errors occurred, the strategy-method group was more likely to ascribe these lapses to modifiable causes such as inattention. Strategy messages signiﬁcantly increased the degree of enjoyment expressed by these students and their willingness to work on the math problems. Finally, those students who originally exhibited the lowest self-perceived competency in mathematics benefited the most from strategy-message training.
Strategy training also appears to increase intellectual self-confidence. One index of self-confidence is the degree to which individuals exercise independence in judging the merits of ideas. Following administration of the Productive Thinking Program, Vernon Allen and I. Levine (1967) gave students false feedback allegedly representing the opinion of their peers regarding the correctness of various answers to a problem. Instructed students were less likely than control students to give up their own ideas simply because they differed from peer-group opinion. The fact that independence of judgment can be encouraged through strategy training is highly signiﬁcant given the importance of self-regulated learning to school reform. Perhaps even greater importance can be attached to these findings in light of Binet’s celebrated definition of intelligence, “Comprehension, planfulness, invention and judgment – in these four words lies the essence of intelligence” (p. 54).
The topic of self-confidence and its encouragement leads to a larger point concerning motivational focus. Not only is having confidence in one’s judgment critical to good thinking, but so, too, (p. 184) is what David Perkins and his colleagues (Perkins, Jay, & Tishman 1993) refer to as thinking dispositions. One such disposition involves being sensitive to situations that can benefit from the application of thinking strategies. Perkins’s advice to teachers regarding ways to enhance such dispositions is illuminating (Tishman, Jay, & Perkins, 1993): “[You] want to find ways to help students to be alert to sprawling and aimless thinking, and sensitive to step-wise thinking opportunities. You might begin to cultivate such sensitivities by modelling them yourself: ‘As I was working on such-and-such a project,’ you might say aloud to the class, ‘I realized my thinking was disorganized”’ (p. 148).
Such informal modeling by teachers can be highly effective in encouraging the proper thinking dispositions. So, too, can formal problem-solving training, as reﬂected in research on the Productive Thinking Program. For example, in one study, instructed students, by a margin of over three to one, went on spontaneously to expand causality. These findings indicate that strategy instruction strengthens the readiness of students to use their minds in productive ways – “discovering, envisioning, and going into deeper questions” — to recall Wertheimer’s phrase (1959) Such willingness and the thinking dispositions that support it should be a prime goal of education.
Another aspect of learning to think is the ability to transfer knowledge and interrelate it from one subject to another. Because no one can possibly anticipate all future contingencies, it is important that students be exposed to knowledge that has broad application. Although not always guaranteeing a solution, general strategies for mental management should at least help in solving problems (see: Innovative Methodologies – Problem Discovery), no matter what the future circumstance. However, not all attempts to demonstrate the transfer value of general thinking strategies have been positive.
For instance, researchers have been largely unsuccessful in demonstrating the benefits of teaching broad heuristics for mathematics problem solving. Students may understand these rules in the abstract but they do not always understand the principles of mathematics well enough to make use of them (Schoenfeld, 1985). Such failures of transfer led Allen Newell and Herbert Simon (1972) to conclude that focusing on broad mental principles is best characterized as a general-weak approach general in that broad strategies are clearly applicable to all problems, but weak because their usefulness for solving a speciﬁc problem may be negligible.
This does not bode well for the arguments in favor of teaching (p. 190) general problem-solving strategies. The prevailing evidence suggests that the key to becoming a good problem solver in a specific area, say accounting involves a very different strategy. It involves simply acquiring lots of specific knowledge about the detailed ins and outs of the particular field.
On the other hand, unfortunately, for all of its undeniable importance, the accumulation of specific content knowledge also seems decidedly limited when it comes to transfer once learned subject-matter knowledge in one domain, say, the ability to play chess well appears to have little positive impact on performance in other domains. Surprisingly, for example, learning to play chess does not insure that students will be better able to solve logic problems. Given these findings, Newell and Simon (1972) characterized the accumulation of specific content knowledge as a strong-specific approach when it comes to transfer-strong in the sense that subject-matter knowledge is a powerful component of effective thought within a given discipline such as biochemistry or astrophysics, but decidedly limited when it comes to solving a wider array of problems outside the discipline.
However, experts in any field revert to broad thinking strategies in an attempt to discover the underlying structure of an unfamiliar problem. They create analogies and metaphors to convert the unfamiliar to the familiar. Experts also construct simple versions of the problem in an effort to detect the workings of the more complicated case. And, almost invariably, they try to identify the specific problem as belonging to a larger class of problems (Adelson, 1981). Additionally, experts establish a context for solving unfamiliar problems.
In the face of unfamiliar territory, general thinking strategies are needed. This problem-framing quality and the fact that future problems are by definition are likely to be novel and unfamiliar justify the emphasis on training for broad problem-solving skills. Brown and Campione (1990) refer to students who possess these general strategies as “intelligent novices.” Intelligent novice may not yet have all the background knowledge needed for exploring a new field in depth, but know how to get it. General and local (content) knowledge are allies not rivals. Both fill important functions in the overall process of problem solving.
When tasks are unfamiliar, overly complicated, or fraught with emotional overtones, then general strategies are most valuable as a starting point. Yet, conversely, the ability of individuals to solve these initially novel problems with increasing sophistication, faster, and with greater assurance depends on the creation of a rich knowledge base of experience that is specific to the particular task. Once this specific knowledge base is in place, then general thinking strategies recede in importance, so that eventually, with enough experience and practice, even highly complex tasks may take on the superficial appearance of simplicity. That is why experts make hard things look so easy (p. 192).
Teaching for Transfer
The teaching of local domain-specific knowledge and broad metacognitive knowledge should be arranged around the discovery and investigation of inherently interesting problems – not just the solving of mindless work sheet problems that trade effectiveness for efficiency.
Such a problem orientation heralds several important changes in the way we must think about school curricula, including the role of content knowledge. Content knowledge must be subordinated to the higher purposes of inquiry (see: Innovative Methodologies – Inquiry-based Learning). Facts should be introduced sparingly, and only as needed. This can be accomplished in several different ways.
• First, students can acquire factual detail in anticipation of problem solving. Here the demands of content acquisition readily conform to the mastery learning methodology (see: Innovative Methodologies – Mastery Learning) in which students are held responsible for various (p. 193) levels of understanding before they advance;
• Second, facts can also be introduced during problem solving, even at the crucial moment of decision making; and
• Third, content acquisition can also proceed after the fact by way of a post-lesson review.
Students can search for, identify, and then learn facts and principles that had not been available earlier which would transform the traditional role of facts from things to think about to things to think with. Content knowledge should be taught in a problem-focused curriculum, especially those with largely cumulative subject-matter. Consider using the logical scaffolding of mathematical knowledge that presumes the progressive step-by-step mastery of propositions, theorems, postulates, and proofs.
But being new to a subject does not mean merely memorizing facts or learning in a “thoughtless” way. The research of Gordon Cavana and William Leonard (1985) demonstrates that acquiring procedural and content knowledge merges comfortably with the goal of self-regulated learning. These researchers distinguish between “proscriptive” (procedural) thinking knowledge and the “discretionary” or managerial aspects of (p. 194) thinking. Most commercial science experiments are predominantly retrospective (presented problems) which are divided into a number of sequential steps that students must complete without variation.
Cavana and Leonard altered these science curricula by allowing students to combine several steps into one, thereby transforming largely proscriptive exercises into partially discretionary tasks over which students could exercise more personal control, independent of both the teacher and textbook. In one experiment that involved changing the curriculum of entire biology departments in three urban high schools, students demonstrated an increasing ability to experience discretion and for longer and longer periods of time (Leonard, Cavana, & Lowery, 1981). Many students who initially could not work without direct guidance for more than fifteen minutes at a time, extended their discretionary capacity to periods of two to three hours by the end of the school year. Moreover, these same students demonstrated a significantly greater understanding of the laboratory concepts involved and produced higher-quality written reports than did students using the unaltered commercial versions of the same exercises.
Research of this kind suggests that effective educational reform lies not in tampering with the inherent organizational structure of subject-matter knowledge, but of arranging content in thought-evoking ways and also in making certain that children realize that what they are learning now about mathematics, science, or grammar has both immediate and future utility. This means that discovered problems must be coordinated closely with the growth and development of the child’s procedural knowledge based so that the act of problem solving itself fulfills the promise of content relevance and also spurs further learning in the belief that this new knowledge, too, will eventually prove useful for some as yet undisclosed purpose or problem.
For all its potential benefits, problem-oriented schooling raises several legitimate concerns such as the possibility that by arranging learning around problem-solving episodes rather than around chapters in a textbook that subject-matter coverage of, say, chemistry or biology will become spotty and uneven. Teachers must sample discovered problems carefully to ensure a wider subject-matter exposure than if students were totally free to choose only those tasks that hold immediate appeal.
However, having once acknowledged the need for caution, a problem-oriented focus is better than those associated with the current hodgepodge approach to content coverage. As things stand, student understanding of most topics is confused plagued by an overemphasis on the trivial to the neglect of the profound, and characterized by wide-ranging misconceptions and misinformation. According to Andrew Porter (1989) this occurs in part because of the widespread practice of “teaching for exposure.”
He reports that at the elementary level most key mathematics concepts receive only the briefest coverage. For example, Porter found that during the entire school year teachers in one sample devoted less than thirty minutes each to 70% of the mathematics topics (p. 196) scheduled for introduction including multi-digit multiplication, number facts, and subtraction with borrowing. Although the reasons for this “once over lightly” approach to content coverage may seem plausible enough – brieﬂy introducing work to be treated in later grades or reintroducing work from the previous years for review – the results are potentially disastrous.
Quite apart from guaranteeing superficial, disjointed preparation, which is bad enough, students may also conclude what is even worse, that knowing very little about a lot of things is better than a deep understanding of a few central concepts. Indeed, there is growing support for the proposition that from an educational perspective it is better to know a few things well than many things superficially, an observation that reminds us of the advice of Alfred North Whitehead (1929) when he anticipated years ago that we must “teach for only a few main ideas . . . which should then be thrown into every combination possible” (p. 14).
Also at fault is the fact that school instruction is not well designed to help students make sense out of complex events. One might suppose that history, a topic that presupposes a rich variegated network of cause-and-effect relationships, would be organized around narrative themes involving people’s reactions to events and the consequences of their reactions. Not so, according to the research of Isabel Beck and Margaret McKeown (1988), who analyzed the treatment of the topic of prerevolutionary America in several elementary school history books.
Apart from the usual ambiguous statements, confusing references, and simple errors of fact, all ‘deplorable’ enough the larger problem was that these texts failed to provide information that would allow students to see connections between events or to understand why events overtake people. For instance, in no case was there a discussion of why previously loyal British colonists would become revolutionaries within one generation. In effect, little was offered that would help students begin to build a sophisticated understanding of American history, so that, when the factual details are long forgotten – it seems the colonists were especially fond of porridge – students will still be able to draw cogent relationships and attach the proper meaning to historical events (p. 196).
A concern about problem-focused schooling involves assigning the highest priority to teaching students how to think. Compared with acquiring content knowledge, at times thinking appears to be enormously inefficient. Solving problems takes time, lots of it – time to reﬂect, define, speculate, and then – true to the convoluted nature of thinking – additional time to redeﬁne the problem, to discard false leads, and sometimes to start over.
Group problem solving is the most cumbersome of all – time out to negotiate with others for their cooperation, time taken to overcome stalemates by searching for the next-most – acceptable alternative for all parties, and even extra time to create controversy deliberately in order to challenge overly simplistic solutions. The importance of this latter function cannot be overstated. For instance, testimony to the presidential commission on the explosion shortly after the launch of the American space shuttle Challenger in 1986 indicated that no one on the launch team wished to voice his concerns about its safety for fear of appearing troublesome or not being a “team player.”
On the face of it, then, teaching thinking appears to confront schools with a cruel trade-off between promoting either broad content coverage or depth of processing. But actually, in the final analysis, this dilemma may be more apparent than real. For one thing, putting a lot of thought into a problem up front by preplanning has been shown to pay dividends in the long run, with better solutions and (p. 198) even greater efficiency in tackling other, similar dilemmas. In effect, teaching for thinking promotes transfer. For another thing, by improving the ability of students to think strategically, they also increase their capacity to learn and to retain more of what they learn. What could be more efficient?
Schools must teach children how to think, not merely what to think. Far from being passive, thinking is an active, constructive attempt by the learner to create meaning. “Thoughtless” education occurs when students do not see the larger utility of what they are learning, when the fear of failure degrades intellectual functioning, and when schools neglect systematic instruction in how to think. Teaching students how to think increases their willingness to think because they are now more likely to see ability as an incremental process, and because learning how to think alters the meaning of failure. Failure now becomes something that can be overcome by analyzing problems better and setting more realistic goals.
The skills of problem discovery, like those of problem solving, are an important part of personal and economic survival, and fortunately, they, too, can be enhanced through systematic instruction. Increasingly, problems of the future will involve the cooperation of individuals, communities, and nations and learning how to share. There is also clear evidence that students can be taught how to overcome obstacles to cooperation. The most important element in preparing students for the future is to teach them how to transfer knowledge, that is, how to apply their thinking skills to new, unfamiliar, or unexpected situations (Covington, 1998, p. 198).