Human research and complexity theory c9 march_0114

Reporter: March ( 林美玲 ) 2011.01. 14 Human Research and Complexity Theory Chapter 9. 人類研究與複雜理論

James Horn, PhD [email_address] Dissertation: The Emergence of Meaning in an Interdisciplinary Learning Environment ： A Qualitative Study of the James R. Stokely Institute for Liberal Arts Education Research Interests ： Complex Learning Communities, Organizational Change, Educational Philosophy and Theory, History of Educational Reforms, Qualitative Research Methodologies Horn, J. (2008). Human research and complexity theory. Educational Philosophy and Theory, 40: 1, 130-143.

Abstract Challenge The new sciences of complexity signal the emergence of a new scientific paradigm that challenges some of the core assumptions of positivism, while offering the potential to develop a new kind of social science that demands both rigour and imagination in coming to understand the emergence and behaviors of social systems and the subsystems that comprise them. Complement The language, concepts and principles of complexity are central to the development of a new science of qualities to complement the science of quantities that has shaped our understanding of the physical and social worlds.

Summary • Introduction • What Complexity Is • Toward a Qualitative Approach to a Science of Qualities • From Simplicity to Complexity • Researching the ‘Edge of Chaos’ • Ethics and Complexity Research Keywords • complexity theory and education • educational research • change • self-organization • autonomous systems

(1) Introduction Gregory Bateson Bateson’s long view seems particularly appropriate to keep in mind now during our early enthusiasms for the new sciences of complexity that are finding entry points to thinking and research questions across many disciplines that range from anthropology (Lansing, 2003) to zoology (Parrish & Edelstein-Keshnet, 1999). Schools as complex organizations Even though our own experiences told us that schools most often are externally controlled and not controlled from within, we believed that an understanding and acceptance of the new sciences could change all that. The democratizing potential that self-organizing adaptive systems The bubbling up of order and freedom derived from local interactions seemed to present the potential realization of a Dewey an agenda begun a hundred years prior.

(1)Introduction Thinking loosely->Stricter thinking there was a worrisome sense that the longer we had to wait for complexity theory to advance beyond the metaphorical stage, the greater the likelihood would be for these ideas to become (for the time being, at least) another ‘fad de jour ’ destined for the dustbin of scientific oddities. Begun to deepen perspectives on understanding This was a fate that seemed undeserving for a set of propositions that, not even fully developed, had already begun to deepen perspectives on understanding, if not predicting, phenomena in the physical, biological, social, and linguistic worlds.

Dangers Scientific or philosophic gestalts do not occur overnight In designing philosophical or empirical studies inside the new complexity box, there could easily develop the temptation to limit research questions to that which could be answered with what we presently know (or don’t know) of complexity, thus sustaining our current level of metaphorical understanding and moving us no closer to rendering ‘general laws of pattern formation’ (Waldrop, 1992) regarding interactive, open systems—systems that are not self-contained but that take in and dissipate energy through interactions. Attempts to resolve ambiguities, or to simplify complexities A second danger resides in attempts to resolve ambiguities, or to simplify complexities, through the use of methodologies and methods that may be rigorous, yet reductive— or comprehensively abstract, though experientially removed from the phenomena to be understood (as in C. Wright Mills’s (1959) criticism of the ‘abstracted empiricism’ of his day).

Toward a clearer delineation of an expanded boundary of science Even so, that seems to be an important place to begin if we are going to move beyond Bateson’s loose thinking stage and toward a clearer delineation of an expanded boundary of science that may, in fact, represent a reclamation of a wider world that has historically been out of bounds for scientific sense-making.

(2)What Complexity Is Complexity focuses on emergent behaviors that result from interactions within and among self-organizing and adaptive systems (Barlow & Waldrop, 1994; Richardson, 2005). Goal The goal of the complexity sciences is to comprehend and explain general laws of pattern formation ( Waldrop, 1992) that signify transitions within autonomous, open systems. Opportunity For educational researchers, the study of learning communities as self-organizing systems offers an opportunity to understand the conditions that are in place when phase transitions occur.

(2)What Complexity The sciences of complexity are concerned with understanding emergent behaviours and behavioural pattern formations that result from interactions of system agents. Invisible hands Historically, the management of social organizations of all types has been maintained by control measures that work to block the capacity of systems to operate autonomously. In many cases, these ‘enforced mechanisms’ (Maturana & Varela, 1998, p. 199) create unhealthy systems that regularly exhibit the pathologies of impaired systems.

How biological systems and social systems differ Biological systems Maturana and Varela (1998) point out that the organism or biological system is sustained by the contributions of its agents whose unrestrained expressions are held in check for the good of the organism. Human social systems Whether they are kindergarten classrooms or adult study groups or corporations, remain viable and capable of growth and change through the continued capacity of interacting members to experience autonomous growth and change. ------------------------------------------------------------------------------------------------------- ‘ The organism restricts the individual creativity of its component unities, as these unities exist for that organism. The human social system amplifies the individual creativity of its components, as that system exists for these components’(Maturana & Varela, 1998, p. 199).

The scientific management movement in education in the early 20 th century were clearly aimed at imposing order upon a system that would otherwise, it was thought, lose energy and eventually disintegrate without such imposition. Those human communities which, because they embody enforced mechanisms of stabilization in all the behavioral dimensions of its members, constitute impaired human social systems: they have lost their vigor and have depersonalized their agents; they have become more like an organism, as in the case of Sparta (Maturana &Varela ， 1998, p.199). To disregard these distinctions between organic and social systems confuses

Historically, these efforts have most often ignored or rejected the possibility that social systems have the capacity to self-organize, adapt, and undergo transitions that lead to sustained, or even higher, levels of effectiveness and efficiency. ------------------------------------------------------------------------------------------------------- Interactive and open social systems , however, depend upon a mix of negative and positive (amplifying) feedback that occur as a result of I-actions of the agents that comprise the system in the light of environmental contexts. These two types of feedback constitute, in fact , the centrifugal and centripetal forces that intermittently move systems toward expansion and contraction , depending, again, on larger environmental circumstances. Interactive and open social systems

Understanding how to allow and sustain self-organizing social systems will require an expansion of the current scientific repertoire used in schools to include ‘a science of qualities that is not an alternative to, but complements and extends, the science of quantities’ (Goodwin, 1994, p. 198). However, the system that began as the focus of understanding inevitably becomes transformed from its naturalistic manifestation into an imposed design that can be rendered by the science used to study it. In order to understand schools and classrooms as the complex environments that they are capable of becoming, we must first allow them to be so. Complements and Extends

Complexity holds out the potential to re-establish the lost link to science that resulted from a denunciation of positivist assumptions. With the lens of complexity, we are able to see whole systems as irreducible examples of knowledge in action, thus establishing a clear link between behaving and thinking, or between ‘data of sense and data of consciousness’ (Lonergan, 1958). Complexity acknowledges the need for a systematic and principled empirical approach to investigating behaviour and thought, while recognizing that every investigation includes an investigator. The recognition of ‘objectivity in parenthesis’ (Maturana, 1988) has profound implications for the ways that humans may come to view the world within which they operate and make knowledge claims. (3)Toward a Qualitative Approach to a Science of Qualities

From wide-ranging studies of dynamical systems, a new dialogue has begun to examine what constitutes evolution, learning, organizations, and life itself. It is an interdisciplinary dialogue that focuses on the self-organization of complex adaptive systems, from the cellular to the social level. While being mapped within various scientific disciplines, these developments ( Wolfram, 2002) offer scientific alternatives to the predominantly reductionist assumptions that have informed science to date. (4) From Simplicity to Complexity

Langton found, through a glitch in his computer programme that occurred as he adjusted interaction rules, what he came to term the ‘lambda parameter’. When interactions were absent, the cellular automata exhibited zero growth. When interactions were sparse, some self-organization was apparent, but soon the dots on the computer grid coalesced into static blobs. Interaction levels were not sufficient to sustain the community. When the interactions between agents were extremely numerous, the computer grid became chaotic, with cycles of accelerated growth followed by mass extinctions. But when the parameters for interactions were established at a certain mid-point, the automata exhibited ‘coherent structures that propagated, grew, split apart, and recombined in wonderfully complex ways’ (p. 226). (5) ) Researching the ‘Edge of Chaos’

Goodwin suggests that the organizational relations must be established for a ‘maximum dynamic interaction’ (p. 184) in order for individual transitions to cascade back and forth through the system, thus producing community as well as individual effects. By doing so, the individual partakes of a community continually enriched by her own individual interactive capacities. (5) maximum dynamic interaction

[Dynamic systems theory] is being used by researchers and theorists for many different levels of analysis, for behavior ranging from the physiologic to the social, and for describing change over time scales from seconds to years. We see this diversity, however, not as a failing of the approach, but indeed as its real strength ... . [W]e are now alert to the pitfalls of explaining too much by single, overarching organization. It seems to us that the future of [dynamic systems theory] will lie with very general principles of process and change, applicable in many domains, over many levels and time scales, but also allowing the multiple local details to emerge from the necessary empirical work (p. xii). (5) Researching the ‘Edge of Chaos’

[Dynamic systems theory] is being used by researchers and theorists for many different levels of analysis, for behavior ranging from the physiologic to the social, and for describing change over time scales from seconds to years. We see this diversity, however, not as a failing of the approach, but indeed as its real strength ... . We are now alert to the pitfalls of explaining too much by single, overarching organization. It seems to us that the future of [dynamic systems theory] will lie with very general principles of process and change, applicable in many domains, over many levels and time scales, but also allowing the multiple local details to emerge from the necessary empirical work (p. xii). [Dynamic systems theory]

The focus is on process not just outcome measures. 2. No agent or subsystem has ontological priority. 3. Task and context, not instructions, assemble behavior. 4. Control parameters are not stationary. [The systematic linking of these practices to synergetic principles’]

In conceiving a research process that is both self-organizing and reflexive, it is necessary to recognize the ontological parity that characterizes the ‘observer community’(Varela, 1979, 1999) comprised of researchers and research participants. Such models would have to be as complex as the original, since the distributed, nonlinear features of complex systems do not allow for the compression of data. Here, this observer readily concedes the difficulty posed in deriving direct causal explanations or predictive proof for complex phenomena within which he is embedded—and the folly of attempting to derive a true understanding if he were otherwise. (6) Ethics and Complexity Research

How then do such possibilities and pronouncements fit with the reality of schools and the needs of teachers and students? I would argue first that every teacher can and should understand the underlying big picture of the new sciences , for with that understanding necessarily comes the realization that she has been placed in charge of a sensitive learning ecology whose directions can be altered by small changes in the boundary conditions and interaction patterns of the classroom. (6) Ethics and Complexity Research

Complexity offers the insight that the study of human systems is best done where it is happening, with students and teachers whose I-actions form the learning patterns that can be shifted without major infusions of motivational energy or continuing intrusions of control measures, either of which stands in the way of growing humans who aspire to freedom and autonomy in the absence of external motivators or control measures.

§ 將複雜性理論加入社會系統中進行革命與想像。人類社會的自我組織與發展需要學術社群的反身凝視，在研究者被研究者對於主客體建構等多重而歧異的關係進行解放與現象的追尋，但也莫忘複雜科學的發展仍需要在嚴謹與具創造力的科學視野下，去重新找尋「未知」作為一個倫理主體的新尺度。

『肉體是虛幻的靈魂是真實的』 by March

Human research and complexity theory c9 march_0114

More Related Content

What's hot (19)

Similar to Human research and complexity theory c9 march_0114 (20)

More from March Lin (11)

Recently uploaded (20)

Human research and complexity theory c9 march_0114