Presenters;

MEHWISH NOOR

RESEARCHING LANGUAGE AS A COMPLEX ADAPTIVE SYSTEM

• Chaos/complexity theory

• Developed from ancient Greek philosophy

• Modern views of mathematics and the physical world

• Explains the nature and characteristics of complex systems

• Defines different types of change

BACKGROUND

• Explores patterns of nonlinearity

• Unpredictability in a complex system

• Avoids marking this as a hybrid state

• The bridging role of complexity theory

• Framing research and practice

PROGRESSING IDEAS

CHAOS

• 'To some physicists chaos is a science of process rather than state, of becoming rather than being' (Gleick 1987 5)

A COMPLEX SYSTEM• Emerges from the interactions of its

components. • (LARSEN–FREEMAN & CAMERON,2008)

COMPLEX SYSTEMS• Often heterogeneous, being made up of both agents

and elements. (LARSEN–FREEMAN & CAMERON,2008)

APPLIED LINGUISTIC COMPLEX SYSTEMS

• Contain many subsystems, nested one within another. (LARSEN–FREEMAN & CAMERON,2008)

COMPLEX SYSTEMS AT ALL LEVELS AND TIME SCALES

• From the social level to the individual levels.

• Milliseconds of neural connections

• Millennia of evolution etc• (LARSEN–FREEMAN & CAMERON,2008)

• va

LARSEN-FREEMAN’S STANCE (1997)

• Learning linguistic items is not a linear process—learners do not master one item and then move on to another. In fact, the learning curve for a single item is not linear either. (p. 151)

• There are no natural divisions or end points in the overall learning process; it is continuous but erratic and the target is a moving one (Larsen-Freeman, 1997).

LEARNING• “We can neither claim that learning is caused by

environmental stimuli (the behaviourist position) nor that it is genetically determined (the innatist position). Rather, learning is the result of complex (and contingent) interactions between individual and environment”.

• (Van Lier ,1996:170)

• A dynamic system

• Emerges and self-organizes from frequently occurring patterns of language use" (p. 111)

• The product of multiple, patterned, and non-linear integrated contexts and times

• Maintains an identity(social and national) in the face of constant change

• CAS Attempts to keep language in a state of status quo in order to keep its standard

LARSEN-FREEMAN VIEWS LANGUAGE

FEATURES OF COMPLEX NONLINEAR SYSTEMS

DYNAMIC COMPLEX NONLINEAR

CHAOTIC OPENSELF

ORGANISING

FEATURES OF COMPLEX NONLINEAR SYSTEMS

Feedback sensitive

Adaptive

Sensitive to initial

conditions

UNPREDICTABILITY• The weather is constantly changing

• Also stays within the boundaries of climate.

• The climate 'We can tell where the system cannot be, and we can identify the states that the system is most likely to be, but we cannot tell exactly where the system will be' (Mohanan 1992 650)

SENSITIVE TO INITIALCONDITIONS

• UG the initial condition of human language

• —it contains certain substantive universal principles that apply to constrain the shape of human languages

• For instance, there are a small number of core phonological patterns that apply to all languages, e g voicing assimilation of obstruent in all languages

• (Mohanan 1992)

• Languages also differ; In English, the voiced consonant assimilates to the voiceless (Salzmann, 2004)

• , whereas in Spanish and Russian, the first consonant assimilates to the second regardless of the voicing feature

• (Lombardi,1996)

• Alan Hewat's novel Lady's Time (1985)

EXAMPLE FROM ENGLISH LANGUAGE

(DST) AS NONLINEAR CHANGE• Usually no straightforward linear cause-effect

relationships where increased input leads to a proportionate increase in the output (e.g. the higher the motivation, the higher the achievement)

BUTTERFLY EFFECT• A huge input can sometimes result in very little or no

impact, while at others even a tiny input can lead to what seems like a disproportionate ‘explosion’

• The system’s behavioural outcome depends on the overall constellation of the system components (Dornyei,2011)

BUTTERFLY EFFECT IN LANGUAGE LEARNING

• The various interlinked components of the system can moderate the impact of any input(both in a positive and negative way ).

• (Dornyei,2011)

LANGUAGE IS ALSO COMPLEX• Satisfies both criteria of complexity

• First, it is composed of many different subsystems phonology, morphology, lexicon, syntax, semantics, pragmatics

• Second, the subsystems are interdependent ,a change in any one of them can result in a change in the others

• (Larsen-Freeman 1989, 1991b, 1994)

LARSEN-FREEMAN AND CAMERON (2008:96)

• First and second languages are both live complex systems which change over time.

• “we change a language by using it”.

FUNCTIONS OF L1 AND L2• Work as attractors.

• An attractor is “a region of a system into which the system tends to move” (Larsen-Freeman and Cameron 2008:50)

• Language development swings between these two poles.

• The language learner is attracted or repelled by one of these poles and out of this cycle of attraction and repulsion emerges a third element, namely, interlanguage.

INTER-LANGUAGE AS A STRANGE ATTRACTOR

• Highly sensitive to initial conditions.

• Small changes in the initial conditions result in unpredictable shifts in language development.

BYBEE’S, VIEW (2006)• The fact is that language forms are being continually transformed

by use .

• Any linguistic representation in the learner’s mind is strongly tied to the experience that a speaker has had with language

• May bear little resemblance to forms that NSs employ or that fit linguists’ categories.

POINT OF DIFFERENCE The behavior of the whole emerges out of the interaction of the subsystems. Thus, describing each subsystem tells us about the subsystems, it does not do justice to the whole of language. (Larsen-Freeman and Cameron ,2008)

LANGUAGE DEVELOPMENT AS DYNAMIC

• Real-time language processing, developmental change in learner language, and evolutionary change in language are all reflections of the same dynamic process of language usage

• ( Bybee, 2006; Larsen-Freeman, 2003; Smith & Thelen, 1993) .

MAIN STANDPOINT

• Researchers' grammars containing static rules do not do justice to the ever-changing character of learners' internal L2 grammars.

CHANGES FROM TRADITIONAL RESEARCH

• (1)The Nature of Hypotheses

• Many complex systems are interconnected and coordinated

• Not always possible to explain behavior, and changes in behavior, by detailing their separate components and roles (Clark ,1997)

• Prediction (or forecasting (Traditional)

• Retrodiction (or retrocasting (CAS)

EXAMPLE GIVEN BY BAK (1997)

• Our explanation of sand pile avalanches is expressed in terms of the structure and stability of the sand pile, rather than in terms of the behavior of individual grains of sand.

CHANGES FROM TRADITIONAL RESEARCH

• (2)Causality

• In the traditional reductionist scenario, the researcher searches for a critical “element whose removal from a causal chain would alter the outcome” (Gaddis, 2002, p.54)

• “Death to the variable”(Byrne,2002)

• Instead of investigating single variables, we study modes of system change that include selforganization and emergence.

• Emergent properties or phenomena occur when change on one level of social grouping or on the timescale of a system leads to a new mode on another level or timescale.

CAMERON AND DEIGNAN (2006) EXAMPLE• The phrase emerged fairly recently in English

• Influenced by social changes and language uses.

• Emergence could not have been predicted using the usual definition of prediction.

• The genealogy of such phrases can be studied and their origin can sometimes be explained in retrospect.

CHANGES FROM TRADITIONAL RESEARCH

• The Process of Co-adaptation

• In first language learning Dynamic alteration in both; child and the caretaker language and behaviours

• In classroom between teacher and the students

• The structure emerges; the lesson

• Multi subsystems at students individual levels

• Emerge new language resources

CHANGES FROM TRADITIONAL RESEARCH

• No Single Independent Variable

• The relationships are reciprocal but not symmetrical

• A web of interacting components

• Entertain Supportive, Competitive and conditional relationships (Van Geert and Steenbeek,in press,p:9)

• Everything is connected to some way to everything else (Gaddis,2002,p.64)

CHANGES FROM TRADITIONAL RESEARCH

• Stability and Variability• A complex system even in a stable mode(attractor)

• Still continuously changing

• Change occurs in their constituents or agents

• In their interaction.

• Stability is not stasis

CHANGES FROM TRADITIONAL RESEARCH

• The Changed Nature of Context

• Context includes Physical, social, cultural, and cognitive perspectives ; inseparable from the system

• Soft assembly

• Learner /learning and the context are inseparable while explaining and measuring

them

CHANGES FROM TRADITIONAL RESEARCH

• Nested levels and Timescales• Systems exist at different levels

• From macro levels to micro levels

• Interconnected

• Systems operate at different timescales

• From milliseconds of neural processing to the minutes and hours of classroom learning

• Lombardi, L. (1996). Restrictions on direction of voicing assimilation: an OT account. University of Maryland Working Papers in Linguistics , 4, 84-102.

• (Zdenek Salzmann, Language, Culture, and Society: An Introduction to Linguistic Anthropology . Westview, 2004)