Education is fundamental to the success of any modern society. It is particularly central during periods of social transition, when the flexibility and adaptibility of populations and institutions are most seriously challenged. In these circumstances, a society's ability to foster new skills, new concepts, and new patterns of learning depends heavily on its ability to renew educational institutions and practices.
There can be little doubt that we now face such challenges, arising from profound shifts in economic and social paradigms. Responding to these challenges requires that we understand three core dynamics. The first is the nature of the techno-economic paradigm shift that creates pressures and opportunities for social change. Although we cannot predict specific economic and social patterns with great confidence, we can learn much from the historic interplay between technological and social innovation (Keating, 1995b; Keating & Mustard, 1993).
The second core dynamic addresses the nature of educational institutions themselves. We need to understand how the current structures and practices evolved, and particularly how they may function as a system resistant to change. Our ability to guide educational transformation in a positive direction is dependent upon our ability to identify the points of leverage for such change (Keating, 1995a).
The third core dynamic focuses on our shifting understanding of the nature of human development. This dynamic is the key focus of the current volume. To the extent that our conceptual structures for thinking about human development and learning are incomplete or misguided, our ability to renew social and educational institutions in a progressive fashion are compromised. As the evidence accumulated in this book attests, the conceptual frameworks for understanding human development are undergoing significant revision (Keating, in press b, c; Task Force on Human Development, 1992). The fundamentally social nature of cognition and learning, the mutual feedback between individual and collective human development, and the role of developmental history in the shaping of human diversity are central themes in this revised understanding. Our ability to make significant progress in education depends on a fundamental shift in society's "folk psychology" of development and learning (Bruner, 1990).
These three core dynamics-social and economic transformation, education's role in that transformation, and our conceptual grasp of fundamental processes of human development-interact to define society's capacity for learning and adaptation. Together they comprise a complex social system that is difficult, but perhaps not impossible, to comprehend. Comprehension is made easier to the extent that we have a broad conceptual framework within which each dynamic is embedded, along with their interrelations. Comprehension of the full system is likely to be essential to progressive change in key social institutions, especially in periods of rapid change. We have been exploring the notion of a learning society as a potentially valuable conceptual framework for this task, including the question of how to build such a society (Keating, 1995a, b, in press a; Keating & Mustard, 1993; Task Force on Human Development, 1992).*
In this chapter, I briefly explore each of these key dynamics using the framework of a learning society as a focus. Based on this analysis, one major issue that requires rethinking is our understanding of human diversity, and how we should address that diversity in educational institutions.
Our traditional views of diversity are not only too limited in their scientific scope, but they are also an inadequate basis for building a learning society (Keating, 1995a, b, in press b, c). We need to find ways to encourage greater breadth and depth of competence throughout the population, in order to support a knowledge-based economy. We also need to accommodate the increasing human diversity arising from population dynamics that generate multicultural and metropolitan aggregations, and from political dynamics that highlight demands for more meaningful inclusion of previously marginalized sectors of the population.
The rapid social and economic changes we are encountering as we approach the twenty-first century present complex and unprecedented challenges to contemporary societies (Keating, 1995b; Keating & Mustard, 1993). Societies now must cope simultaneously with global economic competition, the demand for new competencies in the population, the provision of opportunities for health and well-being across the population, and the maintenance of the social fabric for nurturing, socializing, and educating the next generation. How well these requirements are met forms the foundations for future population health and competence, and hence economic prosperity.
The pace, magnitude, and complexity of social change are often perceived as overwhelming and uncontrollable. This perceived lack of control may in turn distort other perceptions, further diminishing our ability to respond and adapt to change. This core dynamic-accelerating change and decreasing sense of control-makes thoughtful planning and reform difficult to achieve.
Breaking this cycle may be aided by a combined evolutionary and historical perspective that takes note of the fundamentally social nature of Homo sapiens, and of the highly variant patterns of organizing human social life.
We are a social species. We play, work, interact, learn, and reproduce in social groups throughout our lives. We develop in social relationships from the earliest period of life, and we remain dependent longer on caretaking for our survival than any other primate. At our core, then, we need social groups to survive. Our early experiences-most of which occur through social interactions-play a critical role throughout life in how we cope, how we learn, and how competent we become. The nature of the social environment in which we develop is thus a key determinant of our quality of life. Diverse life outcomes-positive and negative-are closely associated with identifiable differences in early social experiences.
In turn, the quality of the human social environment is a function of the competence that is available within the society. The nurture, education, and socialization of new members of the group depend on the skills and commitment of more mature members, and on social arrangements that facilitate high-quality interactions between generations.
Although these demands are not historically new, we face additional challenges unknown even to our recent ancestors. Although we share much in common with our primate cousins, humans are unique in having developed the capabilities of conscious self-reflection, cultural transmission of skills and knowledge through language and other symbolic means, cumulative technological development, and civilization. In evolutionary terms, these are quite recent changes in our lives (Keating, 1995b; Keating & Mustard, 1993).
We can get a better sense of this recency using a calendar-year analogy. If we take 100,000 years as an estimate of the time elapsed since the emergence of fully modern humans, and place it on the scale of a single year, we would note that our species first moved into small urban centers, supported by agriculture, about the end of November, and started an industrial revolution on the afternoon of New Year's Eve. Just a few minutes ago, we launched experiments in instantaneous global communication, information technology, and multicultural metropolism. This recency is further exaggerated if we start our hypothetical year with the appearance of the tool-making hominid line from which we derive, in which case the correct baseline is in the millions of years.
The origins and mechanisms of this evolutionary process remain controversial, but several important features have gained fairly broad consensus. To grasp the first feature, consider the social sophistication of nonhuman primates. Our complex social arrangements and behaviors are not merely a function of cultural experiences; other primates are also skilled social strategists (Tomasello, Kruger, & Ratner, 1993). Much of our intuitive understanding of how to function in groups thus has a lengthy evolutionary history. We added new language capabilities to this already rich social mix, yielding apparently infinite potential for complex communication. Language enables much more complex social communication, and perhaps arises initially out of a need to maintain cohesion in larger groups (Donald, 1991; Dunbar, 1992). The larger group size may have contributed economic benefits of organization and specialization of work, permitting more effective exploitation of harsh habitats and a primitive form of shared risk.
The teaching and learning of special skills were also enhanced by language, and technological development ensued. This unification of instrumental and symbolic functions is apparently unique to Homo sapiens. Vygotsky (1978) proposed this unification of language and tool use as the starting point of fully human intelligence, both phylogenetically and ontogenetically. Humans drew on their increasing symbolic and instrumental sophistication (that is, language and tool use) to establish connections between troops and tribes. We can date the origins of this pattern rather precisely to about 40,000 years ago (Stringer & Gamble, 1993), using as evidence the remarkable explosion of symbolic forms (particularly art) and the rapid spread of more complex stone technologies, which had been previously unchanged for a million years or more.
The accelerating pace of technological and social change is thus based on our unique penchant for collaborative learning across formerly rigid group boundaries. Our ability to encode and enhance this learning through progressively more efficient cultural means-oral histories, formal instruction, writing, and now information technologies-contributes directly to this acceleration. Changes in the means of communication have nontrivial consequences for cognitive activity-how we think, what we know, and how we learn.
A well understood example is the connection between the practice of literacy and the development of logic, argument, reflection, and metacognitive understanding (Cole & Scribner, 1974; Olson, 1994). As literacy spreads, so do literate habits of mind.
Modes of teaching and learning also evolve in response to these broad social and technological shifts, as in the ascendance of "book learning" over hands-on apprenticeship. Because evolutionary changes are by definition trial and error, we cannot be assured that any given historical trend in education is beneficial rather than harmful. Dewey's (1963) cogent criticism of formal education as overly abstract and insufficiently practical spoke to this concern, a concern echoed in many contemporary educational critiques (Bruner, 1960; Lave, 1988; Rogoff, 1990). As the pace of change accelerates, there may be insufficient time for societal adaptation by trial and error. In these circumstances, understanding the core dynamics in order to guide progressive change becomes more critical.
The combination of a new technology for communication with new capabilities in the population creates a potent new medium for discourse among previously isolated groups and individuals, and thus new opportunities for innovation. In concert with changes in social communication (such as language, literacy, and information technology), we have continued to discover new means for extracting material subsistence from the earth. The agricultural revolution first made possible the congregation and settled existence of large groups of humans in specific places over a long period of time (that is, cities). The production demands of agricultural societies were such that a relatively large proportion of the population was needed to provide physical energy directly into the system. Thus only a small portion of the population was directly involved in the acquisition and expansion of knowledge that was potentiated by the agricultural revolution. Literacy and numeracy, for example, remained rare skills over long historical periods-and into the present in less affluent societies.
The next major revolution in social forms occurred very recently. The industrial revolution removed human labor from the direct energy loop required for material production (Rosenberg, 1986) but created a demand for ever more complex arrangements for the division of labor. We see again that the technological innovations were dependent upon concomitant changes in social structures and practices.
These examples illustrate the ongoing, mutually causal interplay between technological and social innovation. This may be difficult to visualize initially, as we are more accustomed to linear or main-effect models, in which an isolated cause yields a specific outcome (Keating, in press c; Senge, 1990). But as we trace four major transformations in our species' history, we can see that changes in technology generate demands and opportunities for changes in societal functioning, and changes in society generate demands and opportunities for technological innovation:
Another such transformational moment seems to be upon us, in the form of existing information technologies-instantaneous global communication, unlimited knowledge storage and retrieval, sophisticated techniques for data analysis and simulation, and artificially intelligent design with robotic manufacture.
Unique among species, then, we have created what systems theorists call an iterative feedback loop between our ways of using material resources and the ways in which we organize our social lives. This new pattern of cultural and social change continually reshapes the ecological habitats in which we live and work-and in which subsequent generations will develop (Keating & Mustard, 1993). Developing an educational system to respond to these demands requires us to attend simultaneously to the broad historical forces that have shaped human development, to the fundamental processes of individual and collective human development, and to the nature of contemporary educational practices.
Criticism of contemporary education in North America has become commonplace, sometimes growing to seemingly desperate levels. Yet little substantive change has occurred. This can be attributed to several sources.
First, and too often overlooked, is the inherent stability of large and complex self-organizing systems. This inertia arises not from the complicity or apathy of educators, as often believed, but rather because the institutions and practices that have evolved over a long period are interlocking and self-sustaining. Our loyalty to a credentialling function, for example, makes it difficult to adapt instruction in ways that would be beneficial to the development of expertise (Keating, 1990a, 1991). Thus making changes to any part of the system implies changes to many other aspects of the system.
This leads directly to the second obstacle: the proliferation of simplistic or faddish solutions that engage energy but ultimately fail to make a difference. One example can be found in programs designed to enhance critical thinking as a simple set of teachable skills-rather than as a coherent way of engaging the world that requires such skills, plus content knowledge, personal dispositions, emotional commitments, and productive patterns of social interaction (Keating, 1990c, 1991). Limited solutions such as these appear to be based on exclusive consideration of main effects-if only this aspect could be changed, then other problems would be solved. Addressing these complex issues requires instead that we understand the dynamics of the full system as it actually functions.
A third obstacle is that proposed solutions often focus on the past rather than the present and future. Conscious adaptation requires anticipation, and will likely fail if changes are designed to solve historic rather than contemporary dilemmas, and if they do not recognize the opportunities for innovation afforded by ongoing technological and social revolutions.
One further and quite major obstacle is the perceived conflict between two ways of identifying the core problem. This conflict is usually portrayed as a forced choice between excellence and equity. Defenders of excellence usually focus on declining standards in education as the culprit, whereas proponents of equity usually see those very standards as the source of the problem.
The first group focuses on how well we are doing as a society in developing the expertise and learning skills that we will need to be globally competitive in an economic sense. The striking differences between North America and Asia in mathematical achievement-a cornerstone skill of the new knowledge-based economies in the view of many observers-are particularly troubling (Stevenson & Stigler, 1992). In addition, the apparent downward secular trend in overall academic performance across successive cohorts of North American students in the past several decades has raised concerns about potential deterioration of educational standards.
One popular response to this concern can be described as "back to basics." The identified culprit is that academic standards have been diluted in several ways: the inclusion of groups who are not well prepared for instruction delivered in the traditional way; the inclusion of topics involving personal or social life experiences, taking time away from academic fundamentals; and the increasing social resistance to any form of grading or judging that could diminish a student's sense of self-esteem, as in the use of "social promotions" for students who have not mastered the material at their current grade level.
This critique is frequently paired with a belief that mainstreaming of special education students is a particular burden, both in how it affects classroom dynamics and in how it draws scarce resources away from children without identified special needs. The preferred solution in this view is to return to a perceived past in which educational practices were undiluted in these ways. The golden past to which this view alludes never existed in quite the way it is remembered.
In any case, merely recreating the status quo ante is unlikely to be sufficient for future needs, not least because the substantive demands are increasing. Facility with rapidly shifting information technologies is an obvious example of a new expectation. Furthermore, our existing educational system was built on the premise that we would likely need only a small elite with the skills to guide the efforts of the mass of population, which needed only a modicum of familiarity with formal learning.
The new economies may well depend on a much greater depth and breadth of population competence in order to function well. When limited skills were economically adequate, a high discard rate could be tolerated-economically, if not humanely. Failure to develop our human resources as fully as possible in the future, however, may hamper our potential to become a knowledge-based economy.
The competing view sees schools as the core of the problem, rather than as any possible route to a solution. In this view, it is the schools themselves that dampen an innate desire for learning, through a relentless message of comparative failure. Historically less powerful groups are systematically told they are less competent, or even incompetent, relative to mostly arbitrary performance standards.
Since the standards are themselves biased, according to this view, the sense of failure is largely illusory and serves mainly to reproduce existing power relations in society. The core problem, then, is too much emphasis on standards, not too little; too much emphasis on excellence and elites, and too little concern with equity and diversity.
The current educational crisis surrounding the teaching of exceptional learners is a prime example of the need for a revised understanding of diversity in human development, and how we can address that diversity productively in formal education (Keating, 1990a, 1991, 1995a; see also M. Clay, this volume, chap. 10).
Several basic assumptions sparked the special education movement that has had a dramatic impact on shaping educational practice since the mid-1960s. The first was a fundamental human rights issue, that all children should have access to appropriate educational experiences. The second arose from the fact that most excluded students could be readily identified by organic deficits, particularly mental retardation, sensory impairments, and physical disabilities. Flowing from this was the adoption of a deficit model, in which special arrangements would be needed to accommodate these previously excluded students.
The provision of special educational resources represented one of the few growth areas in educational budgets. This coincided historically with a growing concern over the increased numbers of children who were performing lower than expected or desired but who did not suffer any overt disability in the organic sense.
The unforeseen consequence of this conjunction of events-quite understandable retrospectively-was a movement to expand the notion of special education to include a much broader range of underperforming students. To qualify for the newly available resources, it was necessary to posit some specific deficit internal to the child. The research on learning disabilities has historically been driven more by this political agenda than by sound scientific evidence (Keating, 1995a; see also Stanovich & Stanovich, this volume, chap. 7).
One dramatic illustration of this peculiar dynamic was the political aggregation of parental pressure groups whose primary goal-securing adequate educational resources for their children-was transformed into an actual goal of having their children declared deficient in some specific fashion, so as to gain access to the resources. That this historical transformation could have occurred so readily is a testimony to the seeming "naturalness" of internal deficit models.
Reconstructing the historical logic is relatively straightforward: Normative educational practices are adequate to accommodate normally developing children. The exclusion of children with overt disabilities is unacceptable; to include them, however, requires the provision of additional educational resources. At the same time, we become concerned with the lack of performance among many children who do not have overt disabilities. If, however, they do not benefit from normative educational practices, then we can assume that they have some covert disability. If we construct such a category of covert disability, then we can justify the provision of resources to those children.
These distortions do not occur only on the political level, however. One of the most frequent research designs in the area of learning disabilities is the comparison of normal children with those who are identified as learning disabled (categorized in that way using widely divergent criteria across studies). Such comparisons usually entail the administration of some cognitive task or test to both groups, with the virtually inevitable result that the LD children are significantly worse. The result then leads to two simultaneous inferences: (1) the LD category is valid; and (2) the observed differences can be causally attributed to the deficiency.
Stated in this simple (but not oversimplified) fashion, the fatuity and tautology of the inferences are obvious. Children who are identified as performing more poorly than average on most tasks will perform more poorly than average on a related task. Very few studies are designed to test a specific hypothesis about the origin or nature of the presumed disability. When more rigorous criteria are used, the proportion of labeled LD children who appear to have specifiable cognitive processing differences is much smaller.
This critique does not imply that children are identical in their fundamental attentional or learning processes. Such differences surely exist, and just as surely are a conjoint product of organic factors (such as infant temperament and attentional processes) in interaction with diverse social and interpersonal environments, beginning with the earliest interpersonal interactions.
But diversity exists throughout the population, not just as a unilinear criterion of competence versus deficit. Our predilection to arrange educational practices as if this unilinear model were actually true is a function of historical contingency, not scientific evidence.
A similarly misguided belief system operates among some proponents of a mainstreaming model of education. This is an unanalyzed hope that mere inclusion of students who have been previously excluded will solve their problems, and have only beneficial impact on the student population as a whole. We need to recognize, instead, how complex a task it is to design a working system that supports developmental progress for all students. It is a task that requires considerable research and innovation on many related fronts (Keating, 1990a, 1995a). This is as true for meeting the needs of developmentally advanced students as it is for students with a wide array of learning difficulties (Keating, 1991, 1995a).
From the perspective of a learning society, we can recognize the legitimate concerns of those who identify excellence or equity as the key issue. We can go a step further, however, and examine ways in which excellence and equity are complementary rather than competing pressures. This is assisted by a revised understanding of human learning and development. Such a revision would focus on the developmental supports for learning that each child requires, and on the fundamentally social nature of learning that affords collaborative learning opportunities to individuals at different levels of expertise (Bereiter & Scardamalia, this volume, chap. 22; Keating, 1990a, 1991).
We can perhaps grasp the impact of these broad social forces for contemporary educational practice through a comparison of educational perspectives that evolved in the industrial age with those that may serve us better in an information age. Table 1 summarizes some of the key contrasts (Keating, 1995a).
Information technology, especially networking, reduces the absolute value of acquired knowledge, because it is so readily available (Keating, 1995b). Advantages thus accrue to those whose goal is knowledge building (Scardamalia & Bereiter, 1993). This is further enhanced when the knowledge building is collaborative rather than strictly within the individual.
| Industrial Age | Information Age | |
| Pedagogy | Knowledge transmission | Knowledge building |
| Prime mode of learning | Individual | Collaborative |
| Educational goals | Conceptual grasp for the | Conceptual grasp and | few; basic skills and algo- | intentional knowledge | rithms for the many | building for all |
| Nature of diversity | Inherent, categorical | Transactional, historical |
| Dealing with diversity | Selection of elites, basics | Developmental model of | for broad population | life-long learning for broad population |
| Anticipated workplaces | Factory models, | Collaborative learning | vertical bureaucracies | organizations |
Source: Keating (1995a)
The goals of course are quite different. In an industrial era, only a few people were required to plan and innovate (the "heads"), whereas the masses were expected merely to execute repetitive tasks (the "hands"). An educational system in such a regime ideally functions as an honest selection mechanism, to ensure that the best and brightest become heads. This never worked well in practice. Schools are deeply embedded in society and thus tended to reproduce social class distinctions based on nonrelevant factors, especially social class and gender.
In any case, this selection mechanism may be far less relevant in an information age. Positions in bureaucracies are far less stable, credentials are less valuable as a guarantee of social status, and the nature of work is changing rapidly. The decimation (or more) of middle management in both the private and public sectors is but one example of this. Enterprises and organizations capable of adapting to rapidly shifting conditions will become more dominant.
To support this, we need to expand competence more broadly and deeply through the population than we have been able to do previously. In this regard, the tensions between excellence and equity, between proponents and opponents of traditional standards, and between regular and special education, take on a new character. We need to base all education on a more explicit and conceptually sophisticated developmental model.
In a previous discussion, I summarized the core conceptual distinctions in this way:
Those individuals who give evidence of being best adapted to current social and educational practices, revealed in test scores and school performance, are defined in the categorical model as most generally adaptable (that is, intelligent) due to a more optimal underlying design. A consequence of this conflation of two quite different meanings is the assumption that educational difficulty is legitimately explained as a failure of adaptability of the student.From a developmental perspective, we would recognize that success in a particular ecological. . . niche is not necessarily a sign of adaptability to a wide range of niches. Moreover, we are more likely to look for ways in which the instructional environment has failed to adapt to the developmental diversity that differential histories inevitably generate. By shifting the onus from a lack of adaptiveness in the child to a lack of adaptiveness in the setting, we can begin a close examination of the ways to design better learning environments, rather than simply demarcating presumed design flaws in the child. (Keating, 1990a, p. 264).
Theories of human intelligence that place the greatest emphasis on the heritability of individual differences stress the importance of evolutionary history (and thus the contextual factors that operate through natural selection) in shaping the distribution of genetic factors that influence phenotypic (observed) diversity (Eysenck, 1988; Galton, 1892/1962). In contrast, theories of intelligence that focus on the diversity that arises from different life experiences emphasize the contextual contingencies that operate on individuals (Hunt, 1961).
This traditional dichotomy between nature and nurture-that is, inheritance or genetic accounts versus environmental or experiential accounts-has often obstructed understanding. Given the stark contrast between these two views of the world, it is not surprising that the conflict between them has been heated, in all spheres-scientific, political, cultural. What is more disheartening is that the scientific argument has not moved much beyond the political one in many respects, even though the inaccuracy of this bipolar debate has been recognized for some time (Anastasi, 1958). Apportioning variance between these competing factors has become more complex as the precision of these estimates increases (Plomin & Thompson, 1988).
For the functioning organism, of course, these influences are never dichotomous, but instead are fully integrated during ontogenesis. A good example of this integration arises from current work that demonstrates the key impact of experiential history on the sculpting of fundamental neural, immune, and hormonal patterns (Cynader, Shaw, Prusky, & Van Huizen, 1990; Suomi, 1991). Historically, less effort has gone toward the construction of robust developmental accounts of how these two substantive influences give rise to the observed diversity in human intellectual performance.
To do so, researchers of both persuasions need to shift their focus beyond the apportionment of isolated effects, toward the more complicated task of describing the dynamic interaction of multiple influences over the course of human development (Anastasi, 1986; Bronfenbrenner & Ceci, in press; Green, 1992).
Some past confusion can also be traced to the failure to distinguish between contextual factors in ontogenesis that are associated with intellectual development in general versus those that are associated with the observed diversity in intellectual accomplishment.
A useful distinction can be drawn here between capacities and capabilities, a distinction that is masked by the omnibus term "mental abilities." Literacy offers a helpful example. It is obvious that the vast majority of humans have the capacity to become literate, given the appropriate experiential contingencies. Previously illiterate populations demonstrate high proportions of literacy with the advent of schooling, rapidly becoming capable of reading.
Due to theoretical assumptions prevailing in the early history of empirical research on human intelligence (for example, Terman, 1916), these two constructs-capacity and capability-were conflated, in the belief that attained capabilities were reliable estimates of fundamental intellectual capacity (Keating, 1990c). Recent efforts to disentangle these notions, in order to achieve purer, more reliable estimates of fundamental capacity independent of ontogenetic influences-such as information-processing capacity or neural efficiency-have generated mixed results (Ceci, 1990; Hunt, 1978; Sternberg, 1990).
We have argued that the case for "pure" information-processing parameters has yet to be made successfully (Keating, List, & Merriman, 1985; Keating & MacLean, 1987). The natural processes of developmental integration make it difficult to disentangle these influences, stressing again the need to examine in much greater detail the nature of human diversity as a developmental phenomenon (Gardner, 1983; Keating, in press b, c).
In summary, the debate in this area has operated as a reverberating cycle between positions labeled as "nature" versus "nurture." Our increasing understanding of the fundamental inseparability of these two broad categories-that is, organisms have built-in structure arising from phylogenetic history; ontogenesis always occurs in a physical and social environment that impacts on development-the continuing devolution of an important question into an either/or decision likely reflects the presence of hidden barriers to progress in our understanding.
Some of the barriers that impede our understanding of human diversity in intellectual functioning arise from overly simple ideologies and methodologies. Theoretical advances in our understanding of developmental processes, and methodological progress in our ability to study such processes empirically, create the opportunity to move these questions beyond the traditional dichotomies.
In so doing, we should first acknowledge the robust empirical evidence about human diversity that we have acquired using traditional models. Among the best established empirical findings in the behavioral and social sciences are the robust covariance structures of performance on a wide range of cognitive and intellectual tasks (Keating & MacLean, 1988). We may usefully remind ourselves how pervasive these covariance patterns are. In a sufficiently heterogeneous population, positive correlations across a wide variety of cognitive tasks are virtually assured. As well, mean increases in performance with age during the childhood and adolescent years are observed on virtually all cognitive tasks (Case, 1992).
In addition to these robust patterns of individual and age covariance, there are of course stable group differences on many measures of cognitive performance. Patterns associated with demographic indicators, including social class, ethnicity, and gender, have been regularly reported. Organic trauma or genetic anomalies, such as brain lesion or Down syndrome (Cicchetti & Beeghly, 1990), are also reliably related to cognitive performance differences. Patterns of individual differences have also been grouped into diagnostic categories, such as learning disability.
What are the sources of this diversity? The empirical regularity of the patterns described above has contributed to a presumption-among some scientists and the public at large-that a simple and overarching design principle must be responsible. Often, this presumption takes the form of a belief in underlying organismic differences (such as neural efficiency, capacity, or power) as the fundamental source of observed differences.
We should hesitate to make this inferential leap. Empirical efforts to isolate cognitive processing variance from knowledge-base variance, and vice versa, have encountered substantial methodological obstacles. The evidence for uncontaminated measures of either hypothetical source remains unpersuasive (Keating & Crane, 1990; Keating, List, & Merriman, 1985; Keating & MacLean, 1987; Morrison, Morrison, & Keating, 1992). Covariance patterns alone, no matter how robust, are insufficient to demonstrate the operation of any specific mechanism.
This example illustrates the confusion that often arises between data structures and inferred mental structures. The two are not the same. Presumably, robust patterns in cognitive performance data must reflect some coherent source, but this does not necessarily imply that there is an organismic structure homologous with any particular data structure. Borrowing from evolutionary logic, we observe the surface similarity but structural dissimilarity between, say, bats and birds, and the surface dissimilarity but structural homology between spiders and crabs.
To get at homologies, we need to uncover the underlying processes and their histories (Keating, 1990a). This entails one further understanding: the impact of experience is also constrained by internal structures that are shaped by both phylogeny and ontogeny. In other words, humans are not infinitely plastic, and remedial experience is not always fully effective.
The historical conflict between dichotomous positions has unnecessarily constrained theory, practice, and research methods that seek to address important questions about human diversity. We need to know more than how to apportion the amount of influence exerted by two competing categories, each of which is so broad as to be almost wholly uninformative. We need to know how human competence and human coping actually develop as self-organizing dynamic systems. We need to move beyond these traditional dichotomies in order to generate a coherent conceptual understanding of developmental diversity that is methodologically rigorous, empirically sound, and practically useful for educational transformation.
The inherited ability and the environmentalist positions on human diversity have often been interpreted as though the main effects were the ones that truly mattered. But both interpretations ignore the central reality: The only truly causal pathways are embedded in the transactions between the organism and the environment over time. Both [correlational and experimental] methods favor main effects over interactions, whereas the development of all aspects of life . . . involves an interaction of heredity with environment. But dissecting that interaction will require a level of detail and precision not now available. (Green, 1992, p. 331)
One problem in pursuing this research agenda is thus its seemingly overwhelming complexity. The number of potentially important factors and their interactions expands exponentially as we take higher-order interactions into account, and even more so if we examine the multiplicative interactions of those factors across time. Beginning with even a small set of factors, we rapidly approach an effectively infinite set of possible causal arrangements, at least some of which will be indistinguishable on the basis of statistical fit to a model (Glymour, Scheines, Spirtes, & Kelly, 1987).
Can we hope to deal with this level of complexity? We must learn to do so, if we hope to address pressing theoretical and practical questions. Specifically, we need to create a developmental methodology for integrating analyses from many sources in a robust fashion (Gould, 1986; Keating, in press c).
Paradoxically, dissecting the interaction should be as interesting to pure nature as to pure nurture types. To be viewed as causal, behavior genetic accounts ultimately require a developmental account of how that genetic variation is translated into behavior. In other words, available behavior genetic evidence speaks to the fact that genetic variation is implicated in behavioral variation, not with how that connection is established.
One possible explanation is that genetic variability codes directly for neural efficiency in some way. Given the fascinating evidence now emerging on neural sculpting and reorganization that occurs as a function of the transaction of the organism with the environment, direct coding for size, capacity, or efficiency is an assumption that no longer seems tenable (for example, Chang & Greenough, 1982; Cynader et al., 1990; Turner & Greenough, 1985). It is also worth noting that heritability varies with the age of the group in which it is examined, suggesting that the developmental routes of genetic expression are unlikely to preserve one-to-one correspondence with particular phenotypic characteristics (Plomin & Thompson, 1988).
Another behavior genetic candidate for the understanding of diversity in competence is temperament, which does show stable variation very early in infancy. But again, the temperament of the infant interacts with characteristics of the primary caregiver (usually the mother), so that a one-to-one correspondence between infant temperament and later behavioral outcome seems implausible. Genetically controlled experimental studies of Rhesus macaques show this interaction quite clearly, in that genetically hyperreactive (and thus highly vulnerable) infant monkeys cross-fostered to experienced and highly nurturant mothers are more likely than normal infants to become group leaders (Suomi, 1991).
To advance our understanding of human diversity, then, we shall need to examine in greater detail the history of interactions between the organism and the environment. In this investigation, our evolutionary heritage, especially our primate histories, are directly relevant. Numerous examples come quickly to mind.
The socially shared nature of much cognitive activity, of increasing practical importance (Resnick, Levine, & Teasley, 1991), implicates interpersonal relationships and social competence. Our primate history as a social species thus plays an important role in competence and productivity (Suomi, 1991). In addition, the major role of emotional aspects in cognition has been emphasized in recent work (Oatley & Jenkins, 1992), which in turn invoke psychoneuroimmune links (Kiecolt-Glaser & Glaser, 1991).
Integrating human development so as to encompass all these histories-evolutionary, cultural, ontogenetic-requires that many specific methods be used. Each of these methods needs to be critically examined for its ability to permit robust inferences, but we should not assume that we can define robustness with paradigmatic criteria.
Progress in methodology has changed the way we can investigate human intelligence (Keating, in press c). To reflect this shift, I often use the term developmental diversity as a more inclusive one than individual differences, which implies a primary origin within the individual, rather than a historical transaction between the person and a cognitively socializing habitat.
What shape might a developmental integration on human intelligence take? Recognizing that history is always contingent, contextualists never predict the future with certainty. But odds now favor efforts to weave these strands into a coherent story of human development, in all its diversity. Our attempt to tell a developmentally integrated story (Keating, 1990c; Keating & MacLean, 1988) begins with the premise that human intelligence is a dynamic system, at two major levels: populations and individuals.
It grows increasingly clear that knowledge of all types-practical, scientific, theoretical-is always a social and cultural product. As advanced information technologies spread, the social nature of knowledge becomes ever more apparent. The emerging picture of science as a collaborative and cumulative discourse captures the essence of one key self-organizing social system. Differences among societies in how well they are able to make use of the social nature of knowledge may determine, in part, how effective they will be in building successful, innovation-based economies.
In other words, socially distributed intelligence may become increasingly central to societal success. It depends in turn on the diversity of talent available in the population and on the ways in which human groups interact to become units of learning.
Human intelligence is also a self-organizing system at the individual level. A handful of critical elements are essential to the story (Keating, 1990c; Keating & MacLean, 1988). A first principle of dynamic systems-behavioral, biological, or physical-is that they display the capacity to become organized over time, even from ill-formed or chaotic origins. An important corollary is that infinitely elaborate and formally elegant structures can arise from simple feedback processes operating over time. This arises from four central features of dynamic systems, two of them describing functions and two others describing the operational context: (1) the process must iterate routinely; (2) the process must have a feedback loop; (3) the context includes internal constraints that shaped the system-for organisms, their phylogenetic and the ontogenetic history to date; and (4) the context sets the external constraints that limit and shape the actual self-organization that takes place (Keating, 1990b; Keating & MacLean, 1988).
These principles can then define a general developmental function. The history of developmental interactions is incorporated into organismic structures. As in the evolution of species, an individual's future is never fully determined by the past, but it is always constrained by it. Several consequences follow from the nonlinear nature of dynamic systems. We should expect causes and effects to be multidimensional, and often mutually causal. Also, the magnitudes of causes and effects will not always be commensurate. Indeed, the timing of even minor events may lead to a cascade of other events whose outcome for the individual was far greater than the seeming magnitude of its origin.
One of the crucial discoveries in recent studies of cognitive development is the fundamental nonindependence of cognitive activities from their content and context. An equivalent, more positive term for this nonindependence is connected, or perhaps even better, integrated cognitive activity. To locate homologous structures in cognitive activity, we need to study its ontogenesis along with its current functioning. This requires much more than looking at the correlation of age with cognitive performance, since that reflects in large part the averaging effects of cognitive socialization environments. We need to study the dynamic interactions among emerging cognitive structures and the cognitive socialization niches within which they develop (Ceci, 1990; Keating, 1990c; Resnick et al., 1991; Rogoff & Lave, 1984). For some time, we have been exploring the developmental processes-especially in infancy, childhood, and adolescence-that underlie competence, both in specific expertise and in general habits of mind.
In seeking to account for the early growth of conceptual knowledge, we need to be aware of Gibsonian phenomenological priors that constrain how we see the world, and how these pre-attuned perceptual patterns are shaped by experiences during infancy into basic conceptual structures (Keating & MacLean, 1988; MacLean & Schuler, 1989). Intuitive conceptions and misconceptions acquired early in life interact differentially with schooling experiences; these interactions are another potent source of developmental diversity (Gardner, 1983; Keating & Crane, 1990).
Understanding these interactions is aided by detailed investigations into the role of automaticity; the organization and content of procedural and declarative knowledge; the function of self-regulating cognitive activities (like metacognitive strategies or control processes); and social, emotional, and motivational factors, all of which influence the development of intelligence. The links among emotion regulation, attention regulation, and performance appear to emerge quite early in development, during the first year of life (Lewis, 1993; MacLean, Keating, Miller, & Keenan, 1995).
We need to study how these various aspects of cognitive activity become coordinated over time as individuals develop expertise and competence (Keating, 1990a; Keating, List, & Merriman, 1985; Keating & MacLean, 1987). One potential outcome of an integrative approach is the detailed description of pathways to the development of expertise (Keating, 1990a). The long-lived controversy between general and specific theories of intelligence, seen in developmental terms, becomes productive rather than unresolvable (Keating & Crane, 1990). For example, even among adolescents who are in the top 5 percent of the general intelligence dimension, there are diverse and highly consistent patterns of competence (linguistic, social, technical) that are also strongly associated with "noncognitive" factors such as goals, future aspirations, out-of-school activities, and perceived self-competence (Matthews & Keating, 1995).
In this context, the metaphor of habits of mind may have several advantages over traditional notions of mental abilities or capacity. First, it presumes no particular structural outcome. Rather than reducing diversity to fit an a priori pattern, it encourages the observation of what fits with what over time. In so doing, it allows appropriate degrees of freedom to the operation of contingent history. Second, it strikes a better balance between the inevitably closed or fixed quality of structures and the apparent plasticity of development. We know a bit about habits-the longer we have them, the harder they are to change-but they are very flexible in the early stages, and are never completely rigid. Third, habits of mind incorporate dispositional, emotional, motivational, and personality variability, a clearly desirable goal (Keating & Crane, 1990; Sternberg, 1989).
We have found it useful to identify two kinds of habits of mind: those that relate to domain-specific expertise and those that are more domain-general. More general habits of mind are those that guide the customary, or more automatic ways in which individuals engage the world. Predilections for perception, thinking, learning, and interacting with others have a significant impact on how individuals acquire and use competence. Even in infancy, such patterns appear to be associated with performance. Nine- and twelve-month-olds who are successful in an object permanence task demonstrated patterns of attention and emotion regulation that are different from those who did not succeed in the task (MacLean et al., 1995). Moreover, these patterns are predictive of cognitive competence and self-regulation four to five years later (Miller, 1995). Later in development, variability in cognitive activities such as attending to and learning from errors (Shafrir, Ogilvie, & Bryson, 1990; Shafrir & Pascual-Leone, 1990), reflective or critical thinking, and intentional learning and knowledge building (Bereiter & Scardamalia, this volume, chap. 22) become central to the growth of competence. These dispositions likely have their origins in early development as well.
These developments are probably closely linked with other important habits of mind, namely coping skills and orientations (Menna & Keating, 1992). These, too, are not merely cognitive but also social and emotional. We may well discover that habits of coping that are most important for health and well-being-maintaining social connectedness and exercising reasonable control over one's choices-are similar to, and perhaps even homologous with the broad habits of mind that shape the acquisition of competence.
It is likely that the most developmentally sensitive period for laying the groundwork of later competence and coping occurs during the infant's earliest social interactions, probably in the first two years of life. Basic habits of mind that guide how we interact with others, how we attend to the world, what we focus our attention on, and how we learn to deal with new situations, are shaped in the context of these key social relationships (MacLean et al., 1995).
Competence in particular domains of experience begins to accrue as well, most likely in the form of self-organizing systems (Keating, 1990b). The observation that expertise is domain-specific has been well documented by many researchers represented in this volume. The tension between accounts that focus on generality versus specificity is a productive one, if we take a developmental perspective (Gardner, 1983, 1991; Keating, 1990a; Keating & Crane, 1990). The developmental interplay between emerging habits of mind of the general sort with the acquisition of specific expertise is the key area of research for understanding human diversity in competence and coping.
In simplest terms, traditional models of human diversity have focused on the question of who had more or less competence, and to what those differences should be attributed. We need to move now toward a developmental model, whose focal questions are different. How are the universal human capacities-for language, social interaction, forward planning, and abstract thinking-translated into attained capabilities? And perhaps most important, how can we arrange the human social environment so as to maximize competence and coping in the population, maintain the valuable diversity of domains of expertise, and create the social frameworks that facilitate productive networks for collaborative learning?
At the most general level, we need to understand how to support the development of habits of mind that are central to building a learning society. Viewed from a broader historical and cultural perspective, it seems likely that engendering those habits of mind will require substantial institutional innovation, especially in education. Linking these changes with other important social innovations is likely to be necessary, especially those which embed educational activities in the community and in the broader social environment (Keating, 1995b, in press a).
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* This conceptual framework has been and continues to be developed as a collaborative effort of the Human Development Program of the Canadian Institute for Advanced Research. I thank CIAR for their generous support in this activity, and the program members of this interdisciplinary team for their generous collaboration: Jeanne Brooks-Gunn, Robbie Case, Max Cynader, Barrie Frost, Clyde Hertzman, Dan Offord, Alan Pence, Chris Power, Tom Rohlen, Steve Suomi, Richard Tremblay, and Doug Willms.
Last updated: June 25, 1996