Table of Contents

• Introduction
• Key Concepts in Chaos Theory
• Criticisms of ISD
• Respecting the Chaos in ISD
• Towards a Get-Real Model of ISD
• Links
• References

Introduction

Chaos theory emerged from mathematics and quantum physics and began influencing the social sciences in the mid 1980s and early 1990s. It offers some profound insights into systems design and could potentially inform the development of a more flexible and holistic instructional systems design process (You, 1993).

Chaos theorists approach systems by first asking the question, what is the underlying, global order of this seemingly random local phenomenon? These "deep structures of order" (You, 1993: p.18; Hayles, 1991) are critical units of analysis for chaos theorists. As Prigogine and Stengers (1984) suggest

Chaos vs Determinism - In her attempt to apply chaos theory to ISD, You likens chaos theory to quantum physics indeterminism and contrasts it with Newtonian determinism. Determinists assume that all events are determined by preceding events (where we are today is a culmination of all of our previous experiences), and are therefore predictable (assuming we know all of those prior events that led up to them). Traditionally, philosophers have argued against determinism with the idea of free will. Chaos theory offers a new perspective, proposing that while global undercurrents may behave in relatively stable ways, local events are too disorderly, complex, unstable, non-linear, and contextually diverse for us to make rational predictions about.

Chaos and ISD - An implication of chaos theory is that while instructional systems development can be understood systematically and linearly in a broad sense (e.g., by understanding the various components of the ADDIE model), it's effect on instruction cannot predictably be determined through linear, systematic processes (e.g., the Dick & Carey model). Instructional design is a dynamic, nonlinear phenomenon... the chaotic nature of it should be respected, not boiled down to simplistic models that have little hope of withstanding the torrent of idiosyncratic context differences.

Key Concepts in Chaos Theory

According to You (1993), there are three conceptual elements that make up chaos theory: sensitivity to initial conditions, fractals, and attractors.

Sensitivity to Initial Conditions

You may heard of the "Butterfly Effect," the idea that a butterfly flapping its wings in Peking can transform storms in New York City. Chaos systems are sensitive to slight changes in the beginning, which over time and through interactions with an almost infinite number of variables, impacts other events (present and future ones) in unpredictable and disproportionate ways. This creates a state in which no two outcomes are the truly the same.

Fractals

A fractal is a geometric term that describes a phenomenon as infinite in detail and infinite in length yet also h also having hidden patterns embedded within it. Chaotic systems are irregular throughout yet they maintain the same degree of irregularity as one goes from local events to global patterns. So, while no two outcomes can be the same, they can have the same general patterns.

Attractors

An attractor is a behavior to which a system is pulled. There are two general kinsd of attractors: strange attractors and constricting attractors.

• Constricting attractors - These forces pull systems inwardly and attempt to limit their behaviors. There are two kinds of contraining forces: point attractors and limit-cycle attractors.

  • Point attractors - Pull systems towards a state of equilibrium (homeostasis)

  • Limit-cycle attractors - Repetitive or cyclical behaviors

• Strange attractors - This force pulls systems apart toward different behaviors

It is the interaction among these three forces that creates a sense of stability or instability in a system. Systems are bound by paramters which set limits on variability, but to the degree that strange attracting forces exist, predicting the behavior of these systems is problematic.

Feedback - Feedback loops are critical components of systems in general (Kowitz & Smith, 1987).

Criticisms of ISD

Instructional systems development (ISD), as the field stands today, is by-and-large a product of mechanistic, deterministic, linear, and reductionist thinking. As chaos theory, systems design, humanist, and constructivist ideas have come to the forefront, there is increasing criticism of the traditional cookie-cutter approach to instructional design.

• Mechanistic - While systems and chaos theorists typically portray human beings as open systems, ISD (dominated by objectivist tenets of cognitive and behavioral psychology) generally treats people as if they are "self-regulating robots or machines" (You, 1993: p. 22). This fails to take into account individual differences in people, their situations, and their surroundings (i.e., contextual differences). A more dynamic conception of our field of practice is needed.

• Deterministic - While chaos theory argues that events vary indeterminally, ISD assumes the existence of widely-appplicable cause-effect relationships that will determine outcomes (given certain conditions or events). This view is naive, if not arrogant. A more humble and realistic approach to learning is necessary.

• Linearity - Most ISD models and theories are based on a proposed chain of cause and effects. While these models and theories may serve to illustrate ideals or general concepts, they typically fail to produce practical results when faced with the chaotic system that is real-life learning.

• Reductionist - Most ISD research attempts to boil down (or reduce) complex relationships to simplistic, descriptive and prescriptive models. When prescriptive, these models are often too rigid, detailed, and constraining for practical use in actual learning contexts. As a result, research-based models typically fail or are replaced with more natural heuristics (rules of thumb).

Respecting the Chaos in ISD

Coming soon

Towards a Get-Real Model of ISD

Coming soon

Links

http://order.ph.utexas.edu/chaos/
Dr. Matthew A. Trump's Chaos Theory tutorial

http://www.wfu.edu/~petrejh4/HISTORYchaos.htm
History of Chaos Theory

http://www.imho.com/grae/chaos/chaos.html

http://www.societyforchaostheory.org/
Society for Chaos Theory in Psychology and Life Sciences

http://www.santafe.edu/~gmk/MFGB/node2.html
Gottfried Mayer-Kress's site about chaos and self-adaptive complex systems

References

Dresden, M. (1992). Chaos: A new scientific paradigm - or science by public relations? An historically oriented pedagogy essay, Part I. The Physics Teacher, 30(1), 10-14.

Hayles, N.K. (1990). Chaos bound: Orderly disorder in contemporary literature and science. Ithaca, NY: Cornell University Press.

Jonassen, D.H. (1990). thinking technology: Chaos in instructional design. Educational Technology, 30(2), 32-34.

Kauffman, S.A. (1993). The origins of order: Self-organization and selection in evolution. New York, NY: Oxford University Press.

Krowitz, G.T., & Smith, J.C. (1987). The four faces of feedback. Performance and Instruction, 26(8), 33-36.

Lorenz, E.N. (1963). Deterministic nonperiodic flow. Journal of the Atmospheric Sciences, 20, 130-41.

Mandelbrot, B. (1983). The fractal geometry of nature. New York, NY: Freeman.

Prigogine, I., & Stengers, I. (1984). Order out of chaos: Man's dialogue with nature. New York, NY: Bantam.

You, Y. (1993). What we can learning from chaos theory? An alternative approach to instructional systems design. Educational Technology Research and Development, 41(3), 17-32.