A Brief Introduction and Overview of Complex Systems
in Applied Linguistics
Joel HENSLEY

Abstract
This overview paper is an attempt to provide a brief background and introduction tocomplex systems theory in applied linguistics as well as a review of the more recent work
being done in the field. It is divided into two sections: developmental and theoreticalbackgrounds of complex systems theory, and a survey of research from a complexity
perspective in applied linguistics. First, a short developmental background of complexity
theory and how it entered applied linguistics is provided. A theoretical background ofsome of the key ideas in complex systems is then discussed. The second half of the paper
begins with an overview of the past 20 years of complex systems work in applied
linguistics which also touches on relevant work in cognitive development. Finally, current
research being conducted in applied linguistics from a complexity approach is presented,
followed by a proposal of future avenues of complexity research which may benefit the
specific area of applied linguistics and the general understanding of human language.
Key Words: dynamic systems theory, complex systems, emergence, language
development

Introduction
The twentieth century saw an explosion of technological and scientific progressunprecedented in human history; for the last 50 years, humanity has both grown and advanced
exponentially, with communication and information more accessible than ever before through the
propagation of computing and the internet. At the same time, through the sheer volume of work
being produced as science and technology have evolved, the various fields have simultaneously
become necessarily more specified and fragmented, where, were science a tree, one branch may
have little idea what the rest of the branches were doing. Similarly, in the field of applied
linguistics, theories and approaches of language acquisition in the past have been varied and attimes conflicting. Do learners have Chomsky’s (1965) built in language acquisition device(LAD)? Do they require Krashen’s (1985) i+1 level of input in order to learn, or perhaps
Schmidt’s (1992) noticing? Does the brain operate more like a computer, storing and processing
information accordingly (McLaughlin & Heredia, 1996)? And what aspect of a language learner(LL) is most appropriate for investigation, their physical brain (psycholinguistics), how they

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formulate and produce grammar (generative linguistics/syntax), how they conceive of andconstruct language (cognitive linguistics), how they form meaning (semantics), or the role ofcontext (pragmatics) or society (sociolinguistics)?
Naturally, to single out only one of the above areas of study as necessary to understandlanguage would be a futile effort; human beings and the societies in which we exist areinterconnected, complex, and never static. In order to truly approach an understanding of humanlearning of any kind, especially language, which is so vital for almost every part of daily life, allaspects of human development must play a part. This begs the question of how to combine thesocial with the psychological, and everything in between, which is no simple feat. Fortunately,
the previous century also saw a new concept making a name for itself. Complexity science,
literally the study of systems with multiple interrelated parts, is an ever-growing approach being
applied across the board: from ecology (Wu & David, 2002) and epidemiology (Galea, Riddle, &Kaplan, 2010) to economics (Westerhoff, 2003) and sociology (Hoffer, Bobashev, & Morris,2009), and many more besides. Indeed, the past 20 years have seen a steadily increasing flurry ofactivity regarding this approach in the field of applied linguistics as well. Complexity theory may
be exactly what applied linguistics needs in order to combine its various sub-disciplines in orderto gain a more encompassing understanding of language and how it is acquired. Even if it seems adaunting task to purposefully embrace the complex, this conceptualization needs to be thoroughly
investigated to determine its value for applied linguistics. While such investigation is beyond its
capacity, this paper is meant to provide a review of the developments in applied linguistics overthe past two decades regarding complex systems as well as an overview of current applied
linguistics research being conducted from a complexity perspective. For those not yet familiar
with complexity theory, brief backgrounds of key developments and concepts in complexity
science are provided to begin.

Developmental BackgroundDue to the nature of this paper, the developmental background of complexity science
provided here is necessarily brief. For a more comprehensive look at the background of complex
systems, dynamics, and their related studies, refer to van Gelder and Port (1995), de Bot, Lowie,
and Verspoor (2007), and Larsen-Freeman and Cameron (2008), the last to which this paper owes
a great deal. Complexity science can be said to have had its foundation laid as far back as Isaac
Newton (Mohanan, 1992), in whose day the inherently complex problem of calculating threeorbiting celestial bodies such as the Earth, its moon, and the sun could not be solved. Still, it was
not until the beginning of the 20th century that complexity science and math began to come into
their own right with the French mathematician Henri Poincaré’s work in non-linear dynamic
systems (Larsen-Freeman & Cameron, 2008). Poincaré proposed a solution to the celestial threebody problem which helped lay the foundations for chaos theory, a branch of mathematics.
However, complexity science’s true flourishing did not begin until after World War II. With
the rise of computers, advances were made in mathematics (Larsen-Freeman & Cameron, 2008),
leading to catastrophe theory and chaos theory, as well as work on cybernetics (Wiener, 1948)
and artificial intelligence (Ashby, 1960). Around the same time, geneticists and biologists were―８
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Joel HENSLEY：A Brief Introduction and Overview of Complex Systems in Applied Linguistics

developing theories to describe complex systems and processes, leading to general systems
theory, dissipative systems exhibiting self-organization, and autopoietic systems which “change
and build new structures while maintaining their identity” (Larsen-Freeman & Cameron, 2008,p.3), such as the human eye. Complex systems were also introduced to meteorology (Lorenz,1963), from which the now famous “butterfly effect” concerning a system’s dependence on initialconditions eventually derived. Synergetics appeared in the 1980s, followed by the application ofcomplex systems theory in the areas of economics, epidemiology, and developmental psychology(Larsen-Freeman & Cameron, 2008). This last area is of particular interest to applied linguistics,
as the two fields share much in common, with applied linguists adapting concepts andmethodologies from developmental psychologists such as Thelen and Smith (1994). In applied
linguistics, one of the first published works concerning complex systems was Mohanan’s (1992)
work on emergent complexity in phonological development. A short time later, Larsen-Freeman(1997) published her seminal paper formally introducing complex systems to the field of applied
linguistics. While researchers in applied linguistics did not immediately latch on to LarsenFreeman’s proposed theory, the field has seen an ever-increasing amount of work from acomplexity perspective.

Theoretical BackgroundAs should be apparent from above, complexity science covers a wide range of fields anddisciplines. Unfortunately, this can cause some confusion when trying to understand the basic
principles of the theory while not inadvertently applying a concept from one field (the edge ofchaos in math, for example) to another where it may or may not actually fit (fashion trends inbusiness, say). This does not render a study of complexity impossible, but merely warrants proper
caution when applying it in new areas. In order to facilitate such an understanding, a short
discussion of important ideas in complexity theory is necessary.
To begin with, a system is complex if it has a variety of multiple interconnected parts “whichconnect and interact in different and changing ways” (Larsen-Freeman & Cameron, 2008, p.26),
making the system dynamical as well. A classic example of a system that is not complex is asingle pendulum swinging inside a grandfather clock. The pendulum swings back and forth on its
pivot in a predictable pattern of motion that does not change. Were you to hang a second
pendulum from the bottom of the first, however, the resulting construction would be a system
exhibiting dynamical properties as the two pendulums interacted with one another. This
dynamical system would also exhibit the property of non-linearity. The position of a non-linear
dynamical system such as the double pendulum cannot be predicted any further than a few time
steps into the future due to the complex nature of its components. In fact, the double pendulum is
an example of a strange attractor, or state of chaos, in which the position of each pendulum neverfollows the same pattern twice, although all of its future positions are dependent on its initial or
current position. It should be noted here that in complex systems theory, chaos does not equal
anarchy or a lack of all order, but refers to a period of continuous unpredictable system change.
However, this is not to say that the two-pendulum system is completely unknowable. The
properties of the system force it to operate within a very definable set of boundaries, essentially―８５―

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the complete circumference of the lengths of the two pendulums added together. The systemcannot operate outside of this boundary, but within its limits it is free to exhibit the full range ofall possible configurations. Additionally, if it were a closed system, then eventually the attachedpendulums will come to a halt at the point to which gravity pulls them. But if the system wereopen, or able to receive energy from outside, then the pendulums could continue to moveindefinitely, albeit in a non-linear manner.
The idea of states mentioned above is another important aspect of complexity theory. All of
the possible configurations of a system make up that system’s state space, and configurations towhich the system is naturally drawn are known as attractor states. For a more visual example
which is also more complex, picture a small rocky island in the middle of the ocean. Maybe theisland has some trees, some weeds and grasses, a thriving insect population, and houses a smallcolony of insect-eating birds. The state space of this island system, since it includes all possible
attractor states, could potentially range from an insect buffet-like paradise for the birds, to, if
something were to cause drastic change, a bald rock sticking out of the ocean whose only
remaining tenants would be the bacteria left behind after the rest have disappeared. The island,though, as an open system existing in nature, exhibits another important feature of a complex,
dynamical system: adaptability. When picturing an ecosystem such as our island, it is easy to
imagine it as a static, stable entity that does not change as long as weather patterns, sunlight, etc.
remain constant. This is not accurate, however, since any complex dynamical system is always
changing. Change, write Larsen-Freeman and Cameron (2008), is “perhaps the most importantfeature” of a complex system (p.25). The island’s ecology is one system, but it is made up of
many interacting subsystems−the bird colony, insect colonies, trees, individual blades of grass,even the cellular structures of each organism−which are always acting on and being acted uponby other agents in the system. Thus, despite the island’s appearance of stability, that very stability
is only maintained through constant adaptation of all the island ecology’s many parts. The
island’s attractor state is actually one known as the edge of chaos (Kauffman, 1995 in LarsenFreeman & Cameron, 2008). A complex adaptive system (CAS) can actually exhibit the greatest
degree of flexibility and stability when it is near chaos. If a system’s attractor state is too strong,then adaptation becomes difficult; likewise, if an attractor state is unstable, then the slightest
nudge may send a system into a state of chaos (Larsen-Freeman & Cameron, 2008).
Barring an outside influence, or perturbation, that is sufficiently strong, well-timed, or wellplaced enough to disrupt the entire system, a CAS’s component subsystems will most often adapt
to the change by entering a new attractor state while the overall system ecology remains relatively
stable. Our island may experience a typhoon, and even lose a tree or two, but its ecosystem will
likely adapt to the new conditions and continue to function much like before. If a perturbation is
sufficiently strong or well-timed, however, then the CAS of the island may be permanently
altered to a new attractor state. For example, if a lightning strike ignited a fire that destroyed all
the trees on the island, the ecosystem may be forced into a chaotic state as it self-organizes until a
new system of subsystems and processes emerges. The system-altering perturbation does not haveto be as dramatic as lightning, though. Because there are so many interacting parts andsubsystems in any CAS, it is not always possible to predict what effect any perturbation may or
may not have. For our island, it may be something as seemingly benign as one too few days of―８６―Joel HENSLEY：A Brief Introduction and Overview of Complex Systems in Applied Linguistics

sunlight which weakens the plant life and causes a chain reaction of changes that continue until
the system can self-organize and a new, possibly very different, order emerges. Such emergence isthe final key concept in this conceptual background.
In order to move away from our useful but hypothetical island, let us use the CAS of ahuman being, in particular, the human mind. In their important work on cognitive development,
Thelen and Smith (1994) describe the emergence of coordinated reaching and grasping in young
children. As the children were developing, several separate systems, such as hand-eye
coordination and the movement of joints, self-organized into a higher-level CAS through which
the children were able to reach out and grasp an object. Until that moment when the various
systems became self-organized, the children were unable to independently perform the action.
Once the new system emerged, the children were capable of grasping objects. Human language
works much the same way since it, too, is a CAS (The “Five Graces Group”, 2009). As a person’s
language develops, whether a child through the stages of their first language (L1) or a learner of
any age through their second (or additional) language, it is affected by the brain’s level ofcognitive development, the frequency and manner of language use, the physical environment, thelearner’s motivation(s), and even the society in which the learner exists (Larsen-Freeman &Cameron, 2008). All of these factors, many of which are CASs themselves, interact to form the
CAS of language in an individual. As the CAS of the LL’s language encounters perturbations, it isconstantly adapting and self-organizing in response. During these system adaptations and selforganizations, previously non-existent characteristics can emerge, such as the common error inchildren acquiring English as their L1 and some adults acquiring it as their L2 who overgeneralize the past tense -ed suffix to all verbs. Despite not hearing caregivers or native speakers
use words such as “goed” or “eated”, the CAS of the learner may produce such ungrammaticalutterances while it exists in an attractor state where it has possibly noticed and internalized the ed suffix but has not yet been exposed to a sufficient noticing and/or frequency of irregular verbs(or in some cases, the previously correctly produced irregular verb forms may have beensuperseded by the newly emergent -ed suffix) (Ellis & Larsen-Freeman, 2006).

Overview of Complex Systems in Applied Linguistics
The application of CAS theory to applied linguistics has really only been going on for the
past 20 years or so. During that time, many ideas have come directly from developmental
psychology, including work by Holland (1995), Thelen and Smith (1994), and van Geert (1991).
Because of this close relationship, this overview will include not only applied linguistic work in
CASs, but applicable research from developmental psychology as well.
Twenty years ago, Pinker and Bloom (1990) published a paper on the evolution of language
and learners’ language systems. They argued that complex human language, or grammar, hasdeveloped as an adaptation for communication, and could have done so according to natural
selection. Pinker and Bloom were dealing with the literal evolution of language, but at the sametime, van Geert (1991) was using the evolution of an ecological system as a metaphor forcognitive and language growth. He was writing about L1 acquisition at the time, but thecomparison of cognitive (language) growth to an ecological or natural system is one that is still―８
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used today. The following year, Mohanan (1992) published his paper applying CAS theory tophonological development. Then came Thelen and Smith’s (1994) book on dynamic systems
theory (DST) in the cognitive development of children, a landmark work which is still extensively
quoted and referenced in modern CAS and DST research.
The late 1990s saw some of the first evidence of CAS entering applied linguistics.
Continuing previous work in cognitive linguistics, McLaughlin and Heredia (1996) wrote about
second language acquisition (SLA) as a cognitive skill where processes are internalized by the
LL’s cognitive system. Their work helped to bestow the proper importance on the cognitive(processing) aspect of SLA, which was later incorporated into the sociocognitive approach argued
for by Larsen-Freeman (2007) and favored by Larsen-Freeman and Cameron (2008). The
following year, Larsen-Freeman (1997) published her seminal work on applying complexity
theory−which she labeled chaos/complexity science−to applied linguistics. In her paper, Larsen-Freeman provides an extensive background of complexity and dynamical systems theory,
addressing (but not limited to) non-linearity, contained unpredictability, chaos, initial conditions,the edge of chaos, restructuring, emergence, adaptivity, and organic language growth. Many ofthese topics have been discussed in the sections above, but reading Larsen-Freeman’s important
paper is recommended to anyone interested in complex systems in linguistics. The following year,
van Gelder (1998) wrote a lengthy defense of applying DST in cognitive science in which heprovided and refuted 12 objections to the dynamical hypothesis. Likewise, another influential
paper furthering the case for applying complexity theory to linguistics was published by Ellis(1998) with a focus on emergence. In it, he called for a connectionist approach to language
learning which is more comprehensive and uses complexity theory to combine the various fields
and disciplines related to learning which are available to applied linguists.
For the next five years, applied linguistics was relatively quiet in regards to CASs andcomplexity theory. However, beginning in 2002, when Larsen-Freeman (2002) wrote a follow-up
paper to her previous work (Larsen-Freeman, 1997) offering complex systems as a way to bridge
the divide between the debate that was ongoing between a sociolinguistic and a cognitive
linguistic approach to language learning, there was a dramatic increase in papers being publishedfrom a complex systems perspective. At the same time, DST work in cognitive development wascontinuing. Van Geert and van Dijk (2002) offered tools for studying intra-individual variability
in human development, what they consider to be the key for any kind of cognitive growth. Also intheir 2005 course book on SLA research, De Bot, Lowie, and Verspoor took a step toward
integrating DST into the field.
In a preliminary small-scale attempt at investigating variation from a complex systems
perspective in five English as a second language (ESL) learners over the course of several
months, Larsen-Freeman (2006) applied some of the tools offered by van Geert and van Dijk
(2002) in analyzing the five learners’ production. Larsen-Freeman was able to demonstrate theimportance of variation through studying both the averaged results for the group as compared tothe individual learners’ actual production. Interestingly, in accordance with van Geert and van
Dijk, Larsen-Freeman discovered that each learner appeared to be progressing through her own
path to acquisition, with production between learners varying widely, implying that, since no two
people’s cognitive systems are the same, the seemingly similar surface language learners arrive at―８８―

Joel HENSLEY：A Brief Introduction and Overview of Complex Systems in Applied Linguistics

may be achieved through rather different paths. Because of this, Larsen-Freeman stressed theimportance of not averaging or smoothing out the variability in inter-individual data, but using it
as an indicator of individual growth. Part of the difference in LLs’ linguistic development,
according to Ellis and Larsen-Freeman (2006), is through the frequency of language use andexposure, which has a direct impact on what emerges from any learner’s cognitive system.
The following year, as the debate between sociolinguistics and cognitive linguistics
continued, Larsen-Freeman (2007) provided a further push toward a combined sociocognitive
approach through complexity theory. At the same time, de Bot, Lowie, and Verspoor (2007)
furthered the previous offering of research tools from van Geert and van Dijk (2002) by applying
DST to SLA using tools developed in other social science disciplines. De Bot, Lowie, andVerspoor also supported combining the social and the cognitive to produce an overall theory oflanguage development through a DST perspective. Some of the same researchers also published asubsequent study (Verspoor, Lowie, & van Dijk, 2008) using DST to investigate intra-individual
variability in language learning. They also called for a DST research methodology in language
development including longitudinal data gathering, dense observations analyzed in-depth, anddifferent kinds of variability on different levels, all of which should be centered around times ofincreased variability, which may indicate cognitive development. Additionally, they found thathigh intra-individual variability is positively related to language learning through thedevelopment of learner strategies. By this time, complex systems theory had advanced in the field
to the point where Plaza-Pust (2008) even called for a rejection of the universal grammar (UG)
paradigm. She based her rejection on language’s emergence through the self-organization of alearner’s system due to substantial evidence being accumulated through use. When enoughsystem-internal conflict has arisen from a lack of equilibrium brought on by increasing
complexity, then the system adapts, or moves into a new attractor state.
Finally, in the past two years, more work is being done on applying complexity theory todifferent aspects of language development and change. Ellis (2008) has proposed a complexitybased process by which language undergoes change based on frequency of use as well as type
and token frequency. He gives the changes that have occurred to produce the reduced form ofgonna in English−despite its separation from the be verb−as an example of this process ofchange. Van Geert (2008) has described language growth logistically as evolutionary steps which
operate under evolution rules in time and limited resources. Furthermore, it was in this same yearthat Larsen-Freeman and Cameron (2008) published their book on complex systems in applied
linguistics. Serving as both an introduction to complexity theory and a demonstration of DST
research in action, the book also provides a series of questions to encourage thought modeling ofcomplexity in applied linguistics, a “complexity toolkit” (Wilson, 2002 in Larsen-Freeman &Cameron, p.229) for conducting research, and a list of eight “[m]ethodological principles forresearching language and language development” (p.241). To date, Larsen-Freeman and
Cameron’s book is the definitive work on complex systems in applied linguistics. However, in a
special issue of the journal Language Learning, the first collection of complex systems researchin applied linguistics was published and begins with a position paper by The “Five Graces
Group” (2009) on language as a CAS, their preferred term. Now that complexity theory has been
introduced in the field of applied linguistics and has started to attract interest, we can only assume―８９―

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that research and work in CAS theory has just begun and that the real test of this approach’s
appropriateness in applied linguistics is now underway.

Current and Future Complexity Research in Applied Linguistics
As mentioned in the previous section, the special issue of Language Learning published in2009 is one of the first collections of complexity-based work in applied linguistics. Now that atheoretical framework has been offered and is being developed, researchers are beginning to
explore how language viewed as a CAS can aid in the understanding of human language learning.
Much of the work provided in that special issue can be divided into two main categories:
language acquisition and development based on its usage (Beckner & Bybee; Ellis & LarsenFreeman; Christiansen & MacDonald; Matthiessen; Mislevy & Yin) and language’s change andevolution as learners interact with the CASs of other people as well as the environment (Blythe &Croft; Boyd, Gottschalk, & Goldberg; Schoenemann; Cornish, Tamariz, & Kirby; Dörnyei, 2009a).
The work covers many different areas and disciplines, which is only appropriate for a theory
based on complexity. Beckner and Bybee, through their corpus analysis of the structure ofcomplex prepositions, concluded that those syntactic structures emerge from local use and, likelanguage itself, can change over time. Their conclusion seems to be in line with Ellis’s idea of
language change through usage (2008) and how by using language we are also changing it, aconcept which Larsen-Freeman and Cameron (2008) likened to the fact that walking through afield affects both the walker and the field. In a similar vein, Ellis and Larsen-Freeman report on
the similarities in the usage-based acquisition of prototypical verb-argument constructions(VACs) between human ESL learners and a computer simulation. They found that, through theuse of simple recurrent networks (SRNs), the simulation was able to exhibit a preference for
prototypical VACs similar to data taken from corpora of native and non-native English speakers,
implying that frequency of use and input play a large part in learners’ SLA. In the realm ofgrammatical recursion in use, Christiansen and MacDonald found that recursion is an acquired
skill, which they demonstrated through the use of simulated models of recursion. The models
were also able to accurately predict grammatical recursion, implying that the skill of recursion is,indeed, acquired through and developed by use. One CAS term which has not yet been touched
on in this paper is iteration. Much of the above usage-based research, as well as language
evolution and change, is related to iteration and iterative learning. The idea of learning throughslightly different iterations of the same situation or activity, or learning something new based onwhat came before, is one inherent to complexity theory in applied linguistics (de Bot, Lowie, &Verspoor, 2007) as well as cognitive development in general (van Geert, 2003).
Research into language as a CAS is, of course, ongoing and promises to continue thus. As
language as a CAS research expands into different linguistic areas, we can expect to see morework being done from a CAS approach. For example, from a theoretical approach, Finch (2010)
has investigated the effects of critical incidents and initial conditions−or the butterfly effect−on
students’ subsequent language learning later in life. Similarly, in her dissertation, van Koert(2010) has used the idea of fractals, or self-similarity, in complex systems to analyze ESL
learners’ writing. She found that learners’ systems, even at different ability levels, exhibited―９０―Joel HENSLEY：A Brief Introduction and Overview of Complex Systems in Applied Linguistics

fractal change according to Zipf’s power law of frequency (Zipf, 1935 in van Koert). The higher alearner’s level, the more variety of constructions, verbs, etc. were employed in writing, which
seems to support the notion that language learning, as a CAS, develops fractally (Larsen-Freeman& Cameron, 2008).
From a more qualitative approach, research has recently been carried out on motivation inlanguage learning as well, based largely on the extensive work of Dörnyei (2000; 2005; 2009b;etc.) in that field. Nitta and Asano (2010) have investigated, as part of an ongoing longitudinal
study, the variation of student motivation in an EFL setting at the university level. From theircomplexity-based research, Nitta and Asano found that many interacting factors, not just one,
contributed to change in student motivation. This is not surprising, in and of itself, but supports
treating language learning as a CAS. Csizér, Kormos, and Sarkadi (2010) have also studied EFL
learners’ motivation, but in combination with dyslexia. They treated learners’ cognitive systems as
coadaptive, and produced a model of LL motivation which captures the dynamic change
exhibited by learners.
Finally, Seedhouse (2010) has investigated interaction in the L2 classroom as a CAS. He
found that L2 classroom interaction does not seem to follow a linear progression, but often
appears to behave dynamically. He also concluded that the interaction was iterative, with one
action preparing the system for the next, the latter being dependent on the former.
As should be evident by this point, DST and CASs are being applied to linguistic research ina wide variety of areas. As this preliminary work is shared, it is encouraging to note that theresults seem to be supportive of applying the CAS theory to language learning and developmentin applied linguistics. It is most likely safe to assume that we will see an increase of research into
language based on DST, CAS, emergentist, connectionist, and usage-based approaches. As muchof the work carried out thus far seems to be centering on a few specific areas−language
evolution, emergence in syntax through usage, and learner motivation−it seems necessary that
CAS research be expanded into other aspects of language and its acquisition. In an attempt to aid
in such an effort, several issues which have yet to be addressed from a CAS perspective will be
introduced below.
First, one of the most challenging issues in an application of complexity theory to language
and language learning research is that of collective variables. When dealing with a complex
system of any kind, even one with fewer components than a human learner, traditional
reductionist cause-effect methodologies are ineffective (Larsen-Freeman, 1997). There exist too
many parameters in a CAS to only investigate a single one and hope to determine its precise rolein the entire system. Instead, what must happen is the determination of collective variables within
the system (Larsen-Freeman & Cameron, 2008). By grouping system parameters together, we
may treat them as one variable, allowing study of that variable’s impact on the system. However,this seems as if it could potentially cause future discord in regard to the effectiveness of a CAS
method; any future research should carefully define and defend its choice of collective variable(s).
Concerning SLA, there are a few areas that have yet to be thoroughly considered that may
yet provide insight into language learning. The interlanguage (IL) development of LLs as they
progress toward a system more closely resembling the surface production of a native speaker is,according to CAS theory, necessarily unique to each individual. However, a CAS approach to the―９１―Journal of the Faculty of Global Communication, University of Nagasaki No．
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effect of a LL’s L1 on their IL system may help to clarify unanswered questions in IL research.
Additionally, comparing the ILs of learners in L2 and FL (foreign language) settings may provide
illumination into the different effects and amounts to which the learning environment contributes
to language development. There are many FL learners around the world who would benefit froma better understanding of how best to create a productive FL learning environment. Furthermore,
if language is a skill (McLaughlin & Heredia, 1996) or, more likely, a set of skills and strategies(Verspoor, Lowie, & van Dijk, 2008) which interact in complex and dynamic ways, then looking
at the interaction of different skills in language use may aid in the understanding of what
cognitive constructs are required in order for successful communication and/or language growth
to occur. If such a skill set were definable, then it may be possible to track its components’development or even teach their use to leaners.
Investigating LLs’ contribution to their own learning may present interesting qualitative
results as well. For instance, form-focused study or instruction may play a positive role in L2
learners’ acquisition beyond childhood. But learning to what extent such a focus on form has alasting effect on a learner’s language system would seem a vital question for LLs in any context.
If language use were determined to be paramount in long-term system-changing growth, thenfocusing on form in FL classrooms too much may be detrimental to LLs. Moreover, sincelanguage learning is one type of cognitive growth which requires both internal and external
resources (van Geert, 1991) as well as restructuring and successful use of strategies, further
research into how these processes take place in SLA seems necessary. If any of these three areas
can be improved through instruction or use, it may be possible to increase the cognitive tools at
learners’ disposal. This, in turn, may be related to positive effects on learners’ language growth.

Conclusion
This paper has attempted to provide an overview of the theory of complexity, itsbackground, and how it is being utilized in applied linguistics. The sections have been necessarily
brief due to this paper’s limited scope, but each was an attempt to provide key concepts anddevelopments in applied linguistics. These concepts and developments may possibly be helping
to alter the cause-and-effect research paradigm of reductionism in linguistic research to one
which embraces complexity and the interconnectedness of all a learner’s many systems which
help to make up language as a CAS that exhibits emergent properties and evolves over time. As
the field of linguistics progresses, it is becoming more and more apparent that all of its various
fields and sub-disciplines are necessary to create a complete, dynamical picture of language. Sucha holistic approach may seem daunting at the onset, but the application of complexity theory tolanguage and language learning may be both the means and the end to a more complete
understanding of human language.

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