Autonomy, language learning, and the brain

Phil BensonMacquarie University

Presentation at JALT 2014 Conference, Tsukuba, Japan

Autonomy – definition

‘…the capacity to take control of one’s own learning…’

Benson, P. (2011) Teaching and Researching Autonomy. London: Pearson. (p. 58)

Controlling what?

Learning management

Learning content

Cognitive processes

AUTONOMY

Control over what?

Learning management

Learning content

Cognitive processes

AUTONOMY

Control over cognition

• …is metacognitive in the sense that it is – not concerned with direct control of behaviour

(learning management/content)

– is concerned with control of the cognitive processes that control behaviour

• … it involves– control over attention

– reflection

– metacognitive (metalinguistic) knowledge

Control of attention‘The human animal is an attentive animal…. Our attention enables us to organize the field in which we are going to act. Here we have the organism as acting and determining its environment. It is not simply a set of passive senses played upon by the stimuli that come from without [the behaviouristview]. The organism goes out and determines what it is going to respond to and organizes that world’

Mead, G. H. (1934). Mind, self and society: The viewpoint of a social behaviorist. Chicago: University of Chicago Press.

How important is control of cognition to a theory of autonomy?

“The nature of the autonomous learner’s psychological relation to the learning process is often described in general attitudinal terms or in terms of capacities for ‘detachment’, ‘critical thinking’, ‘creativity’, and so on. Here, I have hypothesized that it may be described more precisely as a capacity to control certain cognitive processes that are central to the management of language learning’

(Benson 2011: 112)

Neuroscience

• Thought and ideas are physical (Lakoff 2013)

• Mapping behaviour and thinking onto brain activity– electrical activity (EEG) / blood flow (PET) / blood

oxygenation (fMRI)

– Locate activity in regions of the brain / neural networks

• Applications– Educational neuroscience (Goswami 2006)

– Neurolinguistics (deGroot 2011; Ellis 2008)

– Neurosociology (Franks and Turner 2013)

– Neuroeconomics (Camerer, Loewenstein and Prelec 2005)

Neuroscience and decision-making

“The capacity to take long-term consequences of our behaviour into account seems to be the product of our prefrontal cortex, which, tellingly is the part of the brain that is uniquely human.”

Camerer et al. 2005: 39

Controlled vs. automatic processes

Controlled Automatic

Serial (step-by-step)

Deliberative / Explicit

Effortful

Accessible to introspection

e.g., solving a mathematical problem

Multiple and parallel

Reflexive / Implicit

Effortless

Not accessible to introspection

e.g., visual recognition, language processing

Cognitive vs affective processes

Cognitive processes Affective processes

Concerned with ‘yes/no’ questions

Work with affective processes to produce action

Can control affective processes

Concerned with ‘go/no go’ questions

Work with cognitive processes to produce action

Can override cognitive processes

Four quadrants

Cognitive + controlled

Affective + controlled

Cognitive + automatic Affective + automatic

Foor challenges from neuroscience

1. Implicit learning cannot be controlled

2. We exagerrate the role control

3. Decision making depends on affect

4. Control may not lead to good decisions

1. Implicit learning cannot be controlled

• Much brain activity (both affective and cognitive) is automatized and inaccessible to introspection and control

• Controlled processes only come into play when automatic processes are interrupted

• Much of language processing involves automatic processes and is implicit

• Much L2 learning is implicit, though conscious control is also needed to overcome non-optimal L1 implicit processes (Ellis 2008)

2. We exagerrate the role of control

• Introspective access to cognitively controlled processes is much stronger than access to automated processes

• We exagerrate the degree to which we control our behaviour – it is the controlling part of the brain that thinks it is in control

• Brain activity that initiates behaviour is recorded 300 msec before the activity associated with intention

3. Decision making depends on affect

• Cognition is insufficient in itself to cause action without the support of emotion processes

• “The affective system provides inputs in the form of affective evaluations of behavioral options…. It is not enough to ‘know’ what should be done; it is also necessary to ‘feel’ it.” (Camerer et al 2005: 29)

4. Control may not lead to good decisions

• Deliberative thinking blocks access to emotional reactions influences the quality of decisions

• Decision-making draws resources from the cognitive regions of the brain and affects the quality of later cognitive activity

• People who reflect upon and give reasons for their decisions do not necessarily make better decisions.

Recent critiques of autonomy

• Role of English as a lingua franca and in CMC is leading to a shift in emphasis from language learning to language use.

• “Learners can be considered autonomous only if they can meet the increased problem-solving demands the use of English in international and CMC settings presents” (p. 512).

• A shift of emphasis in the definition of learner autonomy away from control of teaching and learning processes (which are best left to the pedagogical expertise of teachers) to control over language use.

Illés (2012)

Recent critiques of autonomy

“The research hypothesis of this study is that the learner autonomy model is no longer pertinent to the learning of English in France today, since language use and implicit learning are already taking place through everyday communicative activities in virtual communities.”

Sockett and Toffoli (2012: 140)

Implications from neuroscience

• Treat findings from neuroscience cautiously – they are often over-interpreted and turn out to be more complex than than they seem

• They support a shift away from rational-deliberative models of autonomy based on planning, decision-making and reflection

• They support a shift towards more intuitive-responsive models that incorporate implicit learning and emotion

• Our models of autonomy should not be bound to the prefrontal cortex; they should account for language learning as a complex process involving both controlled and automatic processes, and cognition and affect

•

References

Benson, P. (2011). Teaching and Researching Autonomy (Second Edition, first published, 2001). London: Pearson Education.Camerer, C., Loewenstein, G., Prelec, D. (2005). Neuroeconomics: How neuroscience can inform economics. Journal of Economic Literature, 43, 9-64.deGroot, A. M. B. (2011). language and cognition in bilinguals and multilinguals. New York, NY: Psychology Press.Ellis, N. (2008). Implicit and explicit knowledge about language. In J. Cenoz and N. H. Hornberger(Eds.), Encyclopedia of language and education (Second Edition), Volume 6 (pp. 1-13). New York, NY: Springer. Franks, D. D. and Turner, J. H. (Eds.) (2013). Handbook of neurosociology. Dordrecht: Springer.Goswami, U. (2006). Neuroscience and education: From research to practice. Nature reviews Neuroscience, 7, 406-413.Illés, E. (2012). Learner autonomy revisited. ELT Journal, 66 (4), 505-513 Lakoff, G. (2013). Neural social science. In D. D. Franks and J. H. Turner (Eds.), Handbook of neurosociology (pp. 9-26). Dordrecht: Springer.Mead, G. H. (1934). Mind, self, and society from the standpoint of a social behaviorist. Chicago: University of Chicago Press.Sockett, G., and Toffoli, D. (2012). Beyond learner autonomy: A dynamic systems view of the informal learning of English in virtual online communities. ReCALL, 24 (2), 138-151.