claim, or a useful metaphor? Rod Ellis’s ideas are shared by Henry Widdowson,
who asks:“What complexity is there that we cannot explain using socio-
linguistic notions of variation and mental schemata as proposed by Uriel
Neisser in the 1960s?”For him, the development of dynamism and com-
plexity does not come as a surprise, since in the social sciences we have
always known that everything changes constantly through the impact of
social and individual factors.“Projections of individuals in interaction has
been common knowledge for quite some time, adapting to all the changing
factors in interaction”, says Henry Widdowson. Rod Ellis indicates that he
is not convinced that this theory will actually help to understand the basic
issues in language learning and teaching, although Diane Larsen-Freeman has
already pointed to iterative adaptation as a way of characterizing language
learning and practices such as iteration, rather than repetition, and teaching
adaptation, as having consequences for pedagogy.
In the last decade a number of books and special issues of journals have
played a role in the development of this approach, including de Botet al.
(2005, 2007), Larsen-Freeman and Cameron (2008), Dörnyei (2009) and Verspoor
et al.(2011). Through these publications and reactions to them a list of the
main characteristics of complex dynamic systems as relevant for SLD have
emerged. The list contains the following characteristics:
CDST is the science of the development of complex systems over time.
Complex systems are sets of interacting variables from which emerges
something novel.
In many complex systems the outcome of development over time can-
not be predicted, not because we lack the right tools to measure it, but
because the variables that interact and their influence keep changing
over time.
Dynamic systems are always part of another system, with systems nested
within other systems, ranging in levels from sub-molecular particles to the
universe.
Systems develop through iterations of simple procedures that are applied
over and over again with the output of one preceding iteration serving as
the input of the next.
Complexity emerges out of the iterative application of simple procedures;
therefore, it is not necessary to postulate innate knowledge.
The development of a dynamic system appears to be highly dependent on
its initial state. Minor differences at the beginning can have dramatic
consequences in the long run.
In dynamic systems, changes in one variable have an impact on all other
variables that are part of the system: systems are fully interconnected.
Development is dependent on resources. All natural systems will tend to
entropy when no additional energy matter or information is added to the
system.
Trends III 89