J.L.Lemke On-line Office

 

AERA 2002
DRAFT / DO NOT QUOTE OR CITE WITHOUT PERMISSION

Complex Systems and Educational Change

 

Jay L. Lemke
City University of New York
Graduate Center
Ph.D. Program in Urban Education

JLLBC@CUNYVM.CUNY.EDU

 

Sources of Information

 http://academic.brooklyn.cuny.edu/education/jlemke (see Ecosocial Dynamics page)

 http://necsi.org/events/cxedk16/cxedk16_3.html (Endicott House Group 3 Report)

 http://syrce.org/news/workshops.html (U Texas/ SYRCE Balcones Springs Reports)

  

NOTE: The following are draft speaking notes assembled from various works-in-progress and selections from the reports of two conference working groups in which I participated (see Sources above). These notes are made available to stimulate discussion and do not represent definitive findings.

Why Complex Systems?

 The hallmark of contemporary challenges to improving education is the unique contemporary combination of diversity, complexity, and scale in modern educational systems.

 We are all familiar with issues of diversity: in age grades; social class and family and community economic resources; national, ethnic, hybrid and hyphenated cultures, values and languages; genders and sexualities; political and educational philosophies, etc. etc.

 We live with but have less well theorized or understood issues of complexity and scale which make it more difficult to design or engineer solutions to educational problems and force us time and again to abandon large-scale reform efforts and return to local solutions. Even our local solutions may not be sustainable, and they may not scale up or transfer out to other populations in the same community, to other communities, or to larger educational systems. We are, quite frankly, clueless about large-scale educational change and largely unable to relate what we do know about local change to district-wide, state, or national efforts.

 Complexity has many definitions. In the simplest sense it means that the elements of a system, the processes which make it behave as it does dynamically, are so tightly coupled and interdependent so that one cannot expect coherent change from acting on only one aspect of the system independently of its connections to others. Frequently this means that within the system there are causal loops, so that linear intuitions about cause-effect relationships are useless except very locally. The whole behaves as more than the sum of its separated parts.

 Complex systems also tend to exhibit the phenomenon of emergence: qualitatively new collective phenomena arise from the possibilities inherent in coherent behavior among many separate parts, processes, or agents. Which ones arise tends to be sensitively dependent on boundary conditions, or in many evolved natural and cultural systems, to be fault-tolerant and relatively stable (sustainable) patterns of organization that parasitize still more stable resource flows and boundary conditions at longer timescales and larger spatial-extensional scales. As a result evolved complex systems tend to be multi-scale systems.

 Scale becomes a problem when it is combined with complexity and diversity. In large complex, diverse educational or other social and ecological systems, what works in one part of the system may not work in another and so may not be sustainable if sustainability requires resource cooperation at a larger scale.

 Extensional scale is not the only issue. Timescales are also critical, and while these two measures of scale often go hand-in-hand, they need not, especially in cultural systems where communication networks can rapidly connect distant points without integrating the whole space on the scale of that same distance. Timescales are more fundamental to system dynamics than are spatial scales or quantity scales per se. Change is about change on some timescale (years vs. centuries). It is about change against the background of other stabilities (decades of stable revenue sources vs. annual budget cycles). Sustainability is about the timescale of persistence of some structure or behavior in a system. Every sustainable system is built up over many more rapidly cycling smaller-scale processes and must exist within some more slowly changing resource environment.

 Educational change is about interrupting sustainable processes and structures with deep embedding in a much larger social-economic-ecological system and fostering the emergence of alternative processes and structures, newly sustainable on comparable timescales. All educational change, all educational interventions take place inside diverse, complex, multi-scale systems.

  

Research Agendas with Practical Relevance

 What changes within the system are most likely to be relevant to curriculum reform? To bringing to students the opportunity to learn new tools for thinking that have emerged from research on complex systems? To providing students with new activities and experiences to aid their learning? To preparing teachers to bring greater insights into learning processes and specific concepts to their work with students? To enhancing the effectiveness of the educational system in promoting problem-posing and problem-solving, model building and model testing, data interpretation and critical questioning of interpretive frameworks and assumptions?  To enhancing the flow of new ideas and practices from innovators (in software, curriculum, pedagogy, assessment, organizational structure) to policy makers and practitioners?

 

                    How is the educational system as a whole driven by external events and pressures such as advances in scientific understanding, the increasing complexity of  problems addressed by communities and societies, changing technologies, and public demands for reform? How is educational change constrained by resource limitations, standardized curricula and testing, or deeply held cultural beliefs?

                    How is educational change enabled or made possible by bringing new kinds of people into contact with one another or utilizing new technologies (e.g. cross-age tutoring, or tele-mentoring)?

                    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 (charter schools,  online courses) create niches for themselves in the educational ecology? Or new spontaneous networks, such as online communication groups of teachers within a school or across the country, affect the rate of educational change?  Or new economic relationships among elements, e.g., software developers, publishers, schools/districts, authors/publishers, ?

 How would we model and analyze issues like these using the concepts and techniques of ecosystem theory, developmental biology, reaction-diffusion chemistry, non-equilibrium statistical mechanics, nonlinear dynamical systems analysis, cellular automata models, artificial life systems, neural networks, parallel distributed computation, agent-based modelling theory, informatics and infodynamics, ?

 It is a common phenomenon in complex systems of many kinds that system behavior is limited because some elements are decoupled from others; interactions that might otherwise be expected to occur are blocked or strongly buffered. There are many examples of this in the present educational system and each one offers an opportunity to unleash educational change by providing a new channel for interaction.

Schools today have very limited and controlled forms of interaction with the surrounding community and even with students' families. There are many researchers in the field of education who are studying various experiments in closer school-community collaboration and new ways in which parents can participate in the life of schools. How can we enhance these studies to examine the potential of such new forms of interaction for accelerating educational reform? How can we focus on system change?

Within the school, there are two classic forms of segregation barriers: those between disciplines and those between grades. What are the actual functions and consequences within the system of these barriers to mixing? Are any of the purported or historical functions still necessary or valid? Apart from complete random mixing, what other forms of organization across disciplines and between age-grades make educational sense, and what would be the likely system consequences of large-scale interaction between teachers of different subjects and students at different ages? Again, there are existing research programs that have examined inter-disciplinary curricula and cross-age tutoring; the experiences of these researchers can provide valuable data and perspectives for models of educational change that focus on creating new couplings between existing system components.

 

Issues of Localization, Scaling, and Sustainability

= what are the local factors to which systemic change models must be adapted to succeed?

= in what ways that are relevant to the adaptation of systemic change models do local educational systems, at different organizational levels and timescales, differ from one another?

= how do cross-instance models successfully adapt to local conditions?

= what are the most important conditions for sustainability of system change on various timescales?

= what are the most important factors in scalability of changes within one organizational level of a system? (scaling out) And in scaling up to higher organizational levels? Across systems?

 

Issues of Formal Modeling 

How well could we design today a 'SimSchool' or 'SimDistrict' school- or school district- simulation program? Not just to model an existing system, but to enable us to create alternative systems and study their evolution over time, their needs and problems, their probable outcomes? What kinds of schools would students design if given access to an appropriate version of this software? And how would they evaluate various designs proposed by others?  Who would we enlist in the team to create such a software package? What research literatures would we want to consult? What is not yet known that would be needed to complete the project?

 

Defining the System 

If we examine all the source institutions that contribute to students' understanding of particular topics within the formal curriculum, we must include informal educational institutions such as science museums and information sources and learning sites afforded by mass media, print publishing, and interactive communication technologies.

 If we look at resource constraints and decision-making bodies, we will add school boards and trustees and state education authorities.

 In social-ecological terms, educational systems are also material and economic systems. Many of their design constraints and political constraints follow more from these properties than from those associated with learning theories.

If we include ourselves within the system, we will consider our roles as teachers and researchers, and the relationship between research institutions and sponsors and the communities which make use of research results.

 Questions for Modeling the system:

                    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 determine the range of dynamical possibilities at the focal level?

                    What are the typical attractors of the focal level dynamics?

                    Under what conditions is each attractor dominant for the (sub-) system?

                    How do new attractors emerge over the history of the system's development and the evolution of this kind of system?

                    Which features of system behavior are determinate and which are not?

                    Which regions of the space of possibilities are accessible and which are not?

                    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 matter, information, and energy do they exchange?

                    How tightly coupled are they and what is the topology of the coupling network?

 

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? 

Concepts such as multi-scale hierarchical organization, emergent patterning, agent-based modeling, dynamical attractors and repellors, information flows and constraints, system-environment interaction, developmental trajectories, selectional ratchets, fitness landscapes, and varieties of self-organization are becoming key tools for qualitative reasoning about complex systems as well as for quantitative modeling and simulation. 

 

                    What are the range of timescales 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), 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?

 

How would we model and analyze issues like these using the concepts and techniques of ecosystem theory, developmental biology, reaction-diffusion chemistry, non-equilibrium statistical mechanics, nonlinear dynamical systems analysis, cellular automata models, artificial life systems, neural networks, parallel distributed computation, agent-based modelling theory, informatics and infodynamics, ?

 

Timescales, Critical Mass, and Capacity Building

                    Successful partnerships evolve over timescales of the order of 5 10 years and require that researchers become familiar with local history and economic and political issues.

                    Partnerships are more likely to be sustained over several years when they engage a critical mass of practitioners (students, teachers, schools), as well as of researchers (faculty, post-docs, graduate students, experienced teacher mentors)

                    Partnerships need to dedicate significant resources to improving professional capacity of all participants.

 

Scalability and Sustainability

Projects attended to issues of scalability and sustainability from their inception onward by considering the following issues:

                    Selecting an appropriate starting unit of change that provides insight into how the overall system operates but which permits one to stage change in an incremental fashion and study it as necessary.

                    Reform efforts scale more successfully when adaptation to local conditions takes precedence over replication of prior successes elsewhere. This adaptation forms the basis of the value added by researchers.

                    Scaling a reform effort up from its initial unit of change to include, for example, a whole grade-level in a school, a whole school in a district, or a whole district probes the weaknesses of any specific reform model and provides opportunities to improve the model and the implementation practices. This stepwise strategy promotes buy-in from skeptics and establishes a culture of continuous improvements.

                    Scaling a model out, to more diverse populations of students, teachers, and schools is as important to sustainability and continuous improvement as scaling up to larger numbers of participants similar in characteristics to those in the initial efforts. Scaling out is likely to identify weak implementation areas.

                    The role of intermediaries, often researchers who interact with multiple components of the school system and community, is critical to tracing the linkages that aid or inhibit the success and sustainability of reform, and engage researchers in the conditions of school life.

                    Reform efforts conducted by researcher-schools partnerships are more likely to be sustained when there is prior assessment of school system and community readiness for change and when incremental changes alternate with periods of reflection, consolidation, and buy-in by all partners, including parents and the wider community [stepwise strategy]

                    The momentum of reform needs to be maintained by continuous dialogue and formative assessment, between periods of innovation and of consolidation of gains, impact analysis, and identification of further needs.


Timescales of education change

 Longest enduring invariant or slowly changing features:

 

Timescale

Phenomenon invariant over this scale

Order of magnitude

10exp10 sec

Teacher-student ratio of 30 +/- 20

o(320) years

 

Thematic period of 1-2 hours; o[10exp3]

 

10e10

Instructional unit of 3-12 months o[10exp7]

320 yrs

 

Teacher-student pairings change 3-12 months

 

5x10e9

Use of textbooks

160 years

 

Frontal, proscenium architecture; single dominant visual focus

 

 

Lecture, question exchange structure

 

3x10e9

Age segregation across age range 5 18 years

100 years

 

Sequential curriculum; uniform content and pacing for all students at a given age

 

2-3x10e9

Curriculum content in many fields

50-100 years

 

 

 

  

Timescales of principal drivers of current reform interventions:

 

Timescale

Intervention driver process

Typical time

10e8

Curriculum reform mandates

3-5 yrs

5x10e8

Curriculum reform implementation

15 yrs

2-5x10e8

Teaching method change mandate, TPD

6-15 yrs

10e8

New assessment mandates

3 yrs

1-3x10e7

Assessment cycles

.5 1.0 year

10e8

Teacher education reform mandates

3 yrs

5x10e8

Teacher preparation change for major fraction

15 years

3x10e8

Funding reform mandate

10 years

1-5x10e8

Expenditure changes

3-15 years?

3x10e8

New technology development

10 yrs

3-5x10e8

Widespread technology adoption

10-15 yrs

  

It seems fairly clear from this analysis that the drivers will not change the targets on timescales shorter than 10x driver timescales, i.e. 50-100 years.

 How does rapid institutional change happen? i.e. o[nearer 10e8 than 10e9]; i.e. 10-20 years rather than 50-100 or more years? 

= through cascading multiplier effects, but these cannot be top-down in large-scale diverse systems because maintaining such a flow-down structure requires counter-productive rigidities which inhibit change in order to maintain themselves; they have to be bottom up, and only succeed through the failure of higher level regulatory mechanisms, cf. carcinomas, epileptic seizures, etc. not usually constructive for the system

 = through massive disruption of the higher levels of organization (e.g. in war, natural catastrophe), permitting radical reorganization at the lower levels, but this also tends to limit the organizational scale of the new systems and so their sustainability; an evolutionary process takes places, with adaptations to higher level stabilities and resource flows becoming new organizational levels and promoting adaptation downwards through constraint, as well as upwards through selection (the selection criteria are mainly set from above)

 = through new couplings that access new potential regions of the dynamics; prior stabilizations often depend on weak coupling between elements at some level (for cross-level cases see below under heterochrony), to contrast with (i.e. information value, algorithmic complexity) other strong linkages; when the coupling matrix is significantly changed, former structures may dissolve and be replaced by new configurations; this is akin to the system of disjunctions in human societies and is often maintained against challenge by naturalizing ideological discourse formations 

= through emergents that arise from intermediate-scale re-organization of activities at the level below, subject to the contraints of and afforded by the stable resources flows at the level above 

= through heterochronic cross-level re-organization; just as on-level (above) coupling matrices define prefered configurational orders in the set of all those allowed by the constraints above and affordances below, so across distant timescales, there can be effects mediated by semiotic artifacts this mechanism particularly needs to be better understood in relation to change.