The educational systems of advanced societies are highly complex, consisting of many components that interact at multiple layers of organization and at different time-scales. The multiplicity of these components and of their loci of control, the diverse nature of the stakeholders--who range from students and their parents to their elected representatives in cities and towns, states and the Federal government--the richness of interactions among these groups, are all essential components of the system's functioning and must be part of any attempts to support, reform or improve it. In their complexity, education systems are similar to other social organizations, and in fact, share aspects of interaction among components with most physical systems of global importance.
The integration of ideas and methods from many disciplines into the study of complex physical and social systems is indeed generating excitement among scientists, policy-makers, and segments of the general public. Concepts and methods enabled by rapid advances of information technologies are enabling us to understand aspects of the real world where events and actions have multiple causes and consequences, and where order and structure co-exist at many different scales of time, space and organization. Within this complexity framework, critical behaviors that were systematically ignored by classical science can now be included as essential elements that account for many observed aspects of our world–for example, global phenomena that require multiple physical, biological, social, and mathematical perspectives.
Education researchers and policy makers have only recently begun to explore how researchers from other fields approach the study of complex systems and how to manage complexity for productive purposes. The number of systemic reform efforts funded by NSF, coupled with other experimental large-scale reform projects funded by the Department of Education, suggest that the time is ripe to consider how to explore the complex nature of the education system as an object of study, since data to move such studies from theoretical discussions to grounded frameworks of analysis that could be used in a predictive manner is now becoming available.
These arguments led a diverse group of scientists (physicists, chemists, biologists, psychologists, sociologists, mathematicians, computer scientists) and educational researchers to propose to NSF a series of meetings to define a common ground that could be used to generate researchable ideas for integrating the field of education research with advances in the study of complex systems in other disciplines. The group first met in June, 1999 and then in May, 2000, to begin to examine the implications of these deep changes for education – in content, teaching, learning and cognition, and for understanding from a fresh perspective that most complex of systems, the educational system itself. This document summarizes aspects of the discussions, and its appendices examine these ideas in more depth, with the fundamental realization that we are at the beginning of an inquiry, where questions far outnumber answers, and where exploration of the nature of the questions is itself an important topic of inquiry.
The preliminary analysis proposed to NSF identified the two roles for complex systems concepts as focus of deliberation. One is complex system concepts as part of content for mainstream education and the other is complex system methods and perspectives as means for the analysis of education itself.
The groups addressed two broad types of questions surrounding the first focus, complex concepts as part of the content of education: (1-a) What kind of complex-systems concepts are important, for whom and for what purposes? (1-b) What is already known about the teaching and learning of such content? Questions regarding the second role (2), the education system as an object of study, centered on how to characterize the multilevel education system as a complex system, and what questions could be posed to probe its workings. The Appendices to this report present a summary of the deliberations of the three groups formed during the meetings. To simplify this document the ideas around pedagogy discussed in group 1-b are integrated with the discussion on content 1-a.
We offer the following executive summary with full understanding that the hard work lies ahead, and requires the collaboration of many other contributors with wider expertise. This report does little more than set the stage for why such work should be undertaken, and ends with some suggestions on how this work might commence.
The motivation for this inquiry arises from the insights obtained from the applications of the new ideas of complex systems that are now appearing in mathematical, physical, biological, and social sciences. Indeed these applications are being integrated into the working conceptual framework of many professions (e.g., engineering, medicine, finance and management) as well as sciences. For example, interdependence and co-evolution in ecosystems, with emergent patterns formed by self-organization, are now seen as equally important as competitive selection in understanding biological evolution. Similarly, interdependence and self-organization in social systems now informs corporate managers' thinking about their employees as well as the relationships among corporations, who then seek synergistic alliances as well as a simple competitive edge. The success of genome mapping has now led to both the need and opportunity to develop an understanding of functional genomics, in which groups of genes—rather than isolated genes--are seen as functional units, such as metabolic or signaling pathways. Some medical researchers are beginning to refocus on both the interdependent biological systems and the psychosocial context of an individual as an integrated system, an area of high importance to educators. The coupling of meteorological, oceanic and human actions in the understanding of such phenomena as El Niño weather and global climatic change is playing an increasing role not only in meteorology, but also in government policy and in financial decision-making. The widespread interest in complex systems strategies has been intensified by the manifest complexity of the global economy and society, and has been accelerated by the growth of the Internet/WWW and the diversifying and decentralized opportunities for communication and collaboration in the day-to-day lives of citizens and organizations of every scale.
The conceptual basis of complex systems ideas reflects a change in perspective about our world that is important for students to develop, as it corresponds to the scientific environment that will exist when they graduate. This perspective emphasizes both the limits of predictability as well as the possibility of understanding indirect consequences of actions taken, both positive and negative, through modeling the interdependence of our world. While complex system-related concepts are embedded in school science, they are not identified or exploited for their unifying capacity across disciplines. Concepts such as multi-scale hierarchical organization, interdependence, emergent patterning, agent-based modeling, dynamical attractors, deterministic chaos, information flows and constraints, system-environment interaction, developmental trajectories, fitness landscapes, and self-organization are becoming key tools for qualitative reasoning about real complex systems as well as quantitative modeling and simulation in the contexts of synthetic systems.
Except for the education of a few highly trained specialists in a few scientific areas, little of the conceptual power embodied in the rapidly developing tools and perspectives of complex, dynamical systems or informatics has reached the educational experience of our citizenry at any level. Moreover, to the extent that these tools and perspectives remain largely absent from educational decision-making and ongoing efforts directed towards education improvement and leadership development– in content, teaching, learning, curriculum structure, assessment, teacher education and credentialling, management, financing, and the many other factors involved in educational improvement, systemic and otherwise– their absence from mainstream education, and the negative impact of this absence, are destined to continue.
The authors share a perspective that this state of affairs will need to change as the impact of changes in science become integrated into the fabric of social life and are moved to ask what changes might be needed and what new understandings might help us now to know how to achieve them. To this end, we addressed issues associated with complex systems as educational content, and those related to complex systems as an analytic tool set for the study of the education system:
The study of complex systems involves experimental, computational, and theoretical approaches for observation, analysis, and modeling (including dynamical simulation). The interplay among model predictions, analysis and observation is crucial for gaining useful insights into the systems studied, and for gauging the usefulness of follow-up activities. And in the service of understanding the education system, relatively recent‘systemic education experiments' and the data they are accumulating provide, for the first time, the possibility of using observational data to test preliminary predictive models of the education system as a complex system.
Three working groups were formed to produce three starting-point documents intended to lay out shared understandings and beliefs and to outline the larger questions that need further investigation. These three working papers accompany this Executive Summary as Appendices. A bibliographic resource was assembled that documents prior and ongoing work in the field of complex systems in education and is included as a fourth Appendix. All materials are available at http://www.necsi.net/events/cxedk16/cxedk16.html
The remainder of this Executive Summary recaps the working papers and closes by suggesting next steps, including calls for the formulation of a series of research initiatives to begin to answer the questions elaborated in the papers, and the possibility of follow-up national conferences.
Across many domains, concepts derived from a complex systems perspective provide organization to the otherwise bewildering properties of diverse complex systems, help create a common framework and language, and help frame the use of dynamic and often highly nonlinear simulations to test predictions and hypotheses. Indeed, the application of these concepts in conjunction with the application of computational models and visually compelling data-driven simulations yields unprecedented means for understanding complex phenomena and relationships, revealing new, sometimes counter-intuitive patterns and contingencies. Such understandings lead to asking new and essential questions and viewing situations from new perspectives. This common framework and language of complex systems also appears to be critical for the ability of individuals and groups to use knowledge and techniques across very different contexts.
Complementing the power of concepts associated with complex analysis and dynamical modeling (such as feedback and multiple causality), is the power of informatics in understanding complex systems. These techniques, that include pattern matching, parsing and tree construction, for example, reveal relationships among elements of complex systems in ways complementary to dynamical understanding. These techniques are a direct result of the very recent advances in the integration of computing and science. Their potential role in education needs to be studied so that students will be ready for the world in which they will live, and not for the world in which we, the Report's authors and readers, studied.
Knowledge of complex systems rests on three foundations: Experiment and observation in the real world; use of computation for modeling and for information search and analysis; and underlying theory about the time-dependent properties of nonlinear systems. It is important for students to understand the concepts of feedback in general and adaptive feedback in particular, and their consequences for the dynamic evolution of systems. The fact that real-world systems have multiple causes and effects and are open to exchange of information, matter, and energy with the rest of the world has consequences that students of all appropriate ages would greatly benefit from understanding. We wish students to learn how all of these aspects of systems emerge from the properties of the system components and their interconnections, and what aspects of particular systems govern what aspects of the behavior of those systems. It would also be very useful to learn how to distinguish between general properties of complex systems and those features that are specific to the system under consideration.
Several different types of computational modeling styles and techniques should be introduced in appropriate context—calculus-based differential equations, difference models, random-walk or stochastic models, and active-agent models and cellular automata, etc.; also randomness, deterministic vs. non-deterministic chaos, thresholds, sensitivity to initial conditions, periodicity, different kinds of orbits, attractors and repellors, and, most importantly, how to interpret the many kinds of phase-space representations used to describe complex dynamical systems. Students, at an appropriate age, and through the use of observations and appropriate technology can come to understand information flows and constraints, multi-scale hierarchical organization, system-environment interaction, developmental trajectories, selectional ratchets, fitness landscapes, and other conceptual tools of complex systems. There is also a need for exposing students to the power of informatics through appropriately constructed computer exercises in pattern matching and data analysis. The WWW can thus be conceptualized and utilized as a complex system of information transfer, of personal and institutional interaction, and a medium in which modeling is done.
As a consequence of working with these concepts, and through serious, sustained experiences in modeling, argument and justification beginning at an early age, students can learn that effects do not usually have single causes, and that causes may be either direct (primary) or indirect (secondary). They can develop experientially based intuitions for the power and, most important, the limitations of systems modeling, simulations and information analysis as applied to understanding real-world complex systems. They can likewise develop a feeling for the complementary use of informatics to cope with those aspects of very large-scale systems that are beyond the scope of detailed dynamics modeling. These basic intuitions are as important for making personal decisions in life and civic decisions in a democratic society as they are for technical work in science, engineering and the professions.
Recent research in student learning has shown that many central concepts of science in general, and of complex systems and nonlinear dynamics in particular, are challenging for most students and are often counterintuitive or conflict with commonly held beliefs. For example, most people expect a linear relationship between the size of an action and its corresponding effect, which conflicts with the sensitivity to initial conditions that is commonly found outside the classroom. Similarly, people tend to favor explanations that assume the existence of central control (e.g., the flight of flocks of geese) and deterministic single causality, even in cases where such a central control is impossible (e.g., traffic jams). People do not understand the mechanisms for feedback, and thus exhibit deep-seated resistance towards ideas describing various phenomena in terms of self-organization, stochastic, and decentralized processes. Similarly, delayed feedback and differing time-scales often require intuitively unexpected timing of actions, e.g., actions to slow an economy or growing system long before the expected need for slowing– or vice versa.
More significant for the future, however, is the fact that almost all the prior research on student learning involved studying students being educated in traditional ways towards the scientific perspectives that are changing with the advent of technology. A major initiative is needed to determine how younger students can learn these ideas over an extended period beginning at an early age with appropriate experiences and instruction. It will also be important to determine what are appropriate learning experiences and instruction activities and to define curricular options, both within and across subject matter domains. Of particular interest is determining how to integrate traditionally important topics as well as new topics in ways that are broadly implementable. In doing that, we seek to use complex systems ideas and methods to unify and render more coherent students' educational experiences in the same ways that these ideas and methods are helping unify and organize knowledge across traditional boundaries. It should be noted that many of the ideas we seek to integrate into formal education are at the core of activities, such as computer games, for which young students have developed informal and intuitive understandings.
Emerging theories of learning and thinking, themselves informed by complex systems analysis of individual and group interactions, will play an important role in designing and researching new means by which new complex systems content may be learned. Such theories integrate the roles of context, experience, and active engagement of learners, as individuals and as members of collaborating groups. In addition, new computational environments, especially computer-based models and simulations explicitly related to (or data-linked to) physical systems – particularly physical systems that are systematically manipulable and experienced by students – provide opportunity to build qualitative and quantitative understanding of key ideas. New multi-person“participatory” simulation environments enable students to act out roles within a simulation and thus to make experientially grounded connections between the individual micro-level and the population macro- level of phenomena. Such modeling and simulation environments also enable instructional designers to render important concepts and their relationshipsexplicit, to control novelty and levels of complication, to vary context systematically while holding underlying structure invariant, and to overcome limitations of scale in space and time, particularly to enable observation and control of self-organizing and long-term emergent phenomena that require large numbers of cycles to become manifest.
All the above research and development agendas must be pursued systemically within a broad educational context, including how teachers, both pre- and in-service, learn science, how new materials and curricula can be developed and implemented in pedagogically significant ways, and how assessments can be produced that document learning in compelling ways consistent with the larger political expectations regarding accountability and standards.
While the U.S. educational system can be narrowly defined as the system of public and private schools and colleges that offer students formal education from pre-kindergarten to college graduation and beyond, ultimately the system must be defined by its dynamics of interaction. Which institutions and social practices, which sources and users of information and material and human resources are tightly enough coupled and interdependent in their behavior that they must be included within the system? Likewise, what are the ranges of time scales characteristic of the critical processes that enable the system to maintain itself? What are its significant levels of organization, not simply or primarily in terms of lines of authority (control hierarchies) or in terms of political geography, but in terms of characteristic structures and characteristic emergent processes and patterns at each level? What kinds of material resource and information flows connect adjacent and non-adjacent levels? How is information transformed, filtered, re-organized, and added to from level to level? How is information-overload avoided by emergent systems for pattern-recognition that extract from large data-flows only what matters for the dynamics of the next higher level?
Formal organizational hierarchies offer one starting point for identifying levels within the core educational system: What would a dynamical analysis propose in terms of different time scales, and what would the units of analysis be? How do brief actions by teachers and students add up to coherent activities over periods of days and months? How do curriculum change processes that occur over periods of years exchange information with classroom activities that occur over periods of minutes? How do learning events in a laboratory or at a computer workstation and in classrooms and hallways add up to a coherent longer-term process of development of facility with a particular concept?
Whatever level of organization or subsystem is the focus of our concerns at a particular point, we can always ask a series of key questions motivated by the highly general perspectives of complex systems theory. What next higher level of organization determines constraints on the dynamics at the focal level? How do all subsystems subject to those constraints interact to constitute the dynamics of the higher level? What degrees of freedom remain at the focal level after the constraints are allowed for? What units of analysis at the next level below interact to constitute units (or processes or patterns) at the focal level? What characteristics of those lower level units (attractors) determine the range of dynamical possibilities at the focal level. How do new attractors emerge over the history of the system's development and its evolution? What manifolds describe the conditions on the range of values of all other parameters that must be met to achieve some value of the parameter of interest?
At a given level of organization, how are the different units and processes coupled with one another? What kinds of information do they exchange? What are the significant branchings, closed loops, and connectivity decompositions? What is "system" and what is 'environment'? And how do system and environment form a supersystem from the viewpoint of some still larger-scale unit or process?
How is the educational system as a whole driven by external events and pressures such as advances in scientific understanding (e.g., changes in content or in understanding of human learning), the increasing complexity of problems addressed by communities and societies, changing technologies, and public demands for reform? How is educational change enabled by bringing new kinds of people into contact with one another? How would educational processes be affected by creating new feedback loops, such as research data, which systematically describes outcomes, back to teachers, students, and parents? How might new educational institutions (e.g., charter schools, online systems) create niches for themselves in the educational ecology, and how do they effect changes in the formal system? Or how do new spontaneous networks, such as online communication groups of teachers within a school or across the country, affect the rate of educational change?
We need to learn how to model and analyze issues like these using the concepts and techniques of other fields that are exploiting complex systems thinking. Such fields range from ecosystem theory and developmental biology to parallel distributed computation and informatics and infodynamics, among others. Today, how well could we design a simulation program to enable us to create alternative systems and study their evolution over time, their needs and problems, their probable outcomes? And how would we as a society evaluate various designs proposed by others? Does data exist that could be used to test such a model of existing systems? Is such data possible? What is not yet known that would be needed to make such a project credible?
The above perspectives offer insights into opportunities, critical points for systemic change, and identify strategies that are unlikely to yield change. For example, it is a common phenomenon in complex systems that system behavior is limited when some elements are decoupled from others and interactions that might otherwise be expected to occur are blocked or diluted. We have rigid segregation between grades, and usually between subject domains, and, most importantly, between teachers and researchers, between schools and their communities. These are examples in the present educational system, and each offers an opportunity to unleash educational improvements by providing new channels for introducing change agents. How can new technological connectivity change these conditions, and what might prevent it from having an impact?
Many sources of expertise need to be engaged in building new complex systems content for education and for studying its learnability and implementability. Scientists from many different areas need to collaborate with educators, education researchers and materials developers (including technology developers) to help define new science education goals, appropriate curriculum, technology and pedagogical options for formal and informal education. Setting the stage for developing research and action agendas on a national scale, including national dialogues presumably supported by appropriate conference gatherings, is a next major step.
Similarly, many sources of expertise need to be engaged in building models and frameworks for a complex systems analysis of our education system, involving both creators of the knowledge and potential users of the knowledge gained:
Communities of this size and scope do not typically arise by themselves, or, if so, may take too long to do so. An important question arises then regarding how to begin. Some major changes in education have had high-profile beginnings at elite higher education institutions in response to dissatisfaction with the status quo (e.g., case study approaches at the Harvard Business School). Others were the result of leadership emanating from a professional community as occurred near the turn of the 20th century with the origins of criteria for medical school education. Others more recently have been the gradual result of extended investments by NSF in standards-based curriculum projects in K-12, where the standards were broadly advocated by educators prior to the investment and which were informed by research over the prior two or more decades, much of which was funded by Federal agencies including the NSF. Some ongoing changes, such as those involving distance learning and collaborative work, are the result of new technology affordances. Some widespread changes, such as the strong move to accountability and assessment, have political origins.
Regarding the development of new content materials and new curricula, we see catalytic promise in the development of highly interactive, compelling instructional modules with wide curricular breadth and the potential of entry at multiple levels of sophistication. Such might be built around a major recent scientific achievement and/or issue, such as the development of the early HIV/AIDS treatment cocktail, or perhaps dynamic models of climate change. We invite the reader to envision such possibilities. We further suggest that a fruitful next step may be to bring together small focused groups to help with the envisioning and design of such exemplars, their fit with current education content standards, and the R&D processes needed to study their learnability and implementability.
Regarding the study of education as a complex system, we see a need for a long term and substantive research initiative involving multiple and competing perspectives and methods derived from the study of complex systems in other domains but informed by members of the communities listed above. We sketch here, as an illustrative and tentative proposal, an example of a kind of analysis, with a focus on multiscale analytic methods, but with no assumptions that the perspective offered and the first-level intuitive analysis is an accurate, complete, or even appropriate, account. Considerable study will be needed to satisfy criteria of accuracy, completeness, data availability, and adequacy, required for a study of the sort tentatively proposed.
As previously noted, complex systems have structure and dynamics at many scales. The purpose of multiscale analysis is to describe the behavior at different scales and the ways they relate to each other, and the environmental forces that affect the system. A multiscale analysis approach also integrates and sheds light on many other complex systems concepts, including interdependence, emergence, complexity, evolution, adaptation, indirect effects, spatio-temporal patterns, networks, and environment-system interactions.
An intuitive multiscale approach would identify the relationships between forces and behaviors of the system at different scales, and their relationship to functional requirements that the system is expected to perform, and opportunities for change. Such an analysis would provide the basis for consideration of a set of problems of the education system and various efforts that have been or are being considered for implementation at the local, state and national level. Such an analysis should also provide key insights into systemic problems and the opportunities for educational reforms that can address them. The authors of this report hope that the call for proposals in Quadrant 4 of NSF's ROLE will provide short-term incentives for researchers to approach in similar manner the hard questions needed to jump-start a productive research community.
We recommend for the next five or more years a continuing series of meetings, supported and organized by various agencies and organizations at the Federal level, including the National Academies, the AAAS, the NIH, with the NSF playing a coordinating and facilitating role through the formation of a broadly participatory and high profile Task Force on Complex Systems in Education. The Task Force would include a small coordinating group to operationalize its activity. With the support of the Task Force, the meetings would address the two broad challenges outlined in this report: Complex systems as new content/organization for mainstream education of our citizenry, and complex systems as means for understanding and continuing to improve our education system.
Beginning as soon as practical, focused meetings of deliberately mixed communities of experts of the sort listed above should lead to specific research initiatives sponsored by various agencies and funded by mixes of public, private and foundation resources. Other larger and higher profile meetings, involving educational leaders and leaders of national science and professional organizations that generate and exploit complex systems knowledge, should be used periodically to assess and to publicize progress on these twin challenges. Versions of these latter meetings might be appended to or integrated with the regular annual meetings of the participating organizations.
 The authors gratefully acknowledge Dr. Nora Sabelli's insight, intellectual support, and editorial assistance throughout this project.
Video of Yaneer Bar-Yam's seminar on Complex Systems Principles and Education: Focusing on Universal Principles and Individual Differences