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Complexity Theory | Research Conduction

Published on May 11th, 2017 | Last updated on November 26th, 2019 by | Category: TESOL / TESL Issues through CALL | No Comments on Complexity Theory | Research Conduction | 86 Views | Reading Time: 2 minutes

Complexity Theory

Complexity theory is closely linked to chaos theory.

  • Complex systems are random, nonlinear, unpredictable, self-organising, and subject to ‘strange attractor’, (i.e. they home in on a pattern that determines the boundaries of the phenomenon).
  • Larsen-Freeman (1997) proposed that language and L2 acquisition are best viewed as complex systems. She identified a number of features of L2 acquisition that justify this analogy: it constitutes a dynamic process characterised by variability, this process is self-evidently complex (i.e. it involves a number of interactive factors. It is nonlinear (i.e. learners do not master one item and then move on to another), the learner’s interlanguage system is self-organising, i.e. it manifests (restructuring), and the learner’s L1 functions as a (strange attractor). Larsen-Freeman’s application of chaos theory is fundamentally emergentist in that it conflates how L2 knowledge is represented with how it is used and develops over time.
  • A complex system is one in which numerous independent elements continuously interact and spontaneously organise and reorganise themselves into more and more elaborate structures over time.
  • Complexity my hold chaos or chaotic behaviours in itself as ‘disorders’.
  • Complexity is characterised by: (a) a large number of similar but independent elements or agents; (b) persistent movement and responses by these elements to other agents; (c) adaptiveness so that the system adjusts to new situations to ensure survival; (d) self-organisation, in which order in the system forms spontaneously; (e ) local rules that apply to each agent; and (f) progression in complexity so that over time the system becomes larger and more sophisticated.
  • The behaviour of self-organising complex systems cannot be predicted, and they do not observe the principle of additivity, i.e. their components cannot be divided up and studied in isolation.
  • Complex systems naturally evolve to a state of self-organised criticality, in which behaviour leis at the border between order and disorder.
  • The same system can display order, chaos, and self-organising complexity, depending on the control parameters.
  • Complexity is a larger phenomenon compared with chaos, i.e. chaotic behaviours may take place within the arena of complexities as ‘disorders’.

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