of study. The study focused on intra-individual variability in accuracy rates
and complexity measures. The study demonstrates several useful CDST
methods and techniques to measure variability, including min-max graphs
and Monte Carlo analyses to elucidate significance in such variability. Word
complexity and sentence complexity develop simultaneously and can be seen
as“connected growers”.
Chan (2015) reports on a CDST study with identical twins in Taiwan who
wrote short pieces of text in English every week over a period of eight
months. The data show that even though the twins were monozygotic and
raised in a similar environment, there were considerable differences between
them over time on a number of aspects. The dynamic correlations of two
types of lexical complexity were described through a mathematical model
(the hidden Markov model), and the directions of the relations between
writing and speaking were not similar among the identical twins.
8.6 Individual differences and CDST
Maybe the area in AL in which CDST is having the strongest impact is
individual differences, and in particular in the study of attitudes and moti-
vation. In the last decade a number of researchers, including Zoltán Dörnyei,
Peter MacIntyre, Kimberley Noels and Emma Ushioda, have systematically
explored the potential for CDST in the study of motivation. Dörnyei (2014)
provides a sketch of the challenges of motivation research since the early
work of Gardner and Lambert in the late 1950s. He shows how the static
and linear approach to motivation proposed by these authors held sway for
many years but was ultimately overcome by the move to a micro-perspective
on motivation that did not treat motivation as a factor that was statically
assessed using surveys. The analyses at the micro level showed the complexity,
interconnectedness and messiness of motivational forces at the individual level.
Early signs of the growing interest in CDST in research on motivation can
be found in Dörnyei and Skehan:
During the lengthy process of mastering certain subject matters, moti-
vation does not remain constant, but is associated with a dynamically
changing and evolving process, characterized by constant (re)appraisal
and balancing of the various internal and external influences that the
individual is exposed to. Indeed, even within the duration of a single
course of instruction, most learners experience afluctuation of their
enthusiasm/commitment, sometimes on a day-to-day basis.
(2003: 617)Dörnyei (2014) argues that three initiatives cleared the way for a non-linear
systems approach to SLD: emergentism (e.g. Ellis and Larsen-Freeman 2006),
Dynamic Systems Theory (e.g. de Botet al.2007) and Complexity Theory
(Larsen-Freeman and Cameron 2008). These converging strands led to a new
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