INFORMATION PROCESSING IN PSYCHOLOGY AND SLA

Information processing emerged in the field of psychology in the 1970s, out of the so-called cognitive revolution of the late 1950s. Initially a reaction against behaviourist theories that could only offer stimulus–response explanations for

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human learning, it became the dominant psychological paradigm of the last third of the twentieth century. In a nutshell, the human mind is viewed as a symbolic processor that constantly engages in mental processes. These mental processes operate on mental representations and intervene between input (whatever data get into the symbolic processor, the mind) and output (whatever the results of performance are). Performance, rather than behaviour, is a key word in information processing theories. This is because inferences about mental processes can only be made by inspecting what is observable during processing while performing tasks, rather than by inspecting external behaviour in response to stimuli, as behaviourists used to do.

Several key assumptions made by information processing psychologists have been embraced in current SLA research about cognition. First, the human cognitive architecture is made of representation and access. Second, mental processing is dual, comprised of two different kinds of computation: automatic or fluent (unconscious) and voluntary or controlled (conscious). Third, cognitive resources such as attention and memory are limited. Let us unpack each principle in some detail for a better understanding of what information processing stands for.

Information processing theories distinguish between representation (or knowledge) and access (or processing). Bialystok and Sharwood Smith (1985) used a library metaphor to explain this distinction to their SLA audience: ‘knowing what is in the library, plus how the contents are classified and related to one another, must be distinguished from retrieving desired information from the books at a given time’ (p. 105). Linguistic representation is comprised of three kinds of knowledge: grammatical, lexical and schematic or world-related. New L2 knowledge is stored in the mind and has to be accessed and retrieved every time it is needed for use in comprehension or production.

Access entails the activation or use of relevant knowledge via two different mechanisms known as automatic and controlled processing. Canadian language psychologist Norman Segalowitz (2003) compares the two modes of processing to the difference between an automatic and a standard shift car: ‘an automatic shift car changes gears without deliberate intervention by the driver, in contrast to a standard shift car which requires the driver to perform a manual operation’ (p. 383). Unlike cars, however, which are built by manufacturers to function as either automatic or standard shift from the outset, human cognition is supported by both automatic and controlled processing. Information processing psychologists believe that all human perception and action, as well as all thoughts and feelings, result from the interaction of these two kinds of processing.

Automatic processes require small effort and take up few cognitive resources, and therefore many automatic processing routines can run in parallel. During automatic processing, cognitive activation is triggered bottom up by exogenous sources in the environment (something outside the processor, that is, some aspect of the data in the input or environment). By contrast, controlled processing is activated by top-down, endogenous sources (by something inside the processor, that is, by voluntary, goal-directed motivation in the individual’s mind), and it is handled by what we call the central executive. We summon controlled processing

when we intentionally set out to control behaviour, for example, when no automatic routines have been learned yet because the problem is new (as in a new language) or in the face of some kind of problem encountered during automatic processing (as when surrounding noise makes us strive to understand the few disconnected sounds that we can gather from our interlocutor). In such cases, we let our central executive system intervene to ‘control’ the processing task.

Controlled processes therefore allow us self-regulation, but they require a lot more effort and cognitive resources than automatic processes, and thus cannot operate in parallel; they are serial. For this reason, controlled processing is subject to a bottleneck effect. When we voluntarily attend to one thing, we need to block out the rest. If several demands are competing for controlled processing, they will be prioritized and certain processes will wait in line, so to speak, while only one is being executed. This is what we call a limited capacity model of information processing. The model predicts that performance that draws on controlled processing is more variable and more vulnerable to stressors than performance that draws on automatic processing. Therefore, a widely employed method in the study of automaticity is the dual-task condition, where the researcher creates processing stress by asking participants to carry out two tasks simultaneously, a primary task and a distracting task. Under this dual-task pressure, because the distracting task consumes attention away from the primary task, performance on the main task may become variable and vulnerable. If this happens, it is taken as evidence that the participant is relying on more controlled processing and therefore has not yet reached automatization on the performance called by the primary task.

5.2 THE POWER OF PRACTICE: PROCEDURALIZATION AND

AUTOMATICITY

A particular kind of information processing theory, called skill acquisition theory, has been fruitful in guiding SLA efforts since the mid-1980s (e.g. Bialystok and Sharwood Smith, 1985; McLaughlin, 1987). The most influential version has been adopted from the early formulations of cognitive psychologist John Anderson’s Adaptive Control of Thought theory (Anderson, 1983), although his most recent version of the theory goes well beyond traditional information processing notions (Anderson, 2007).

Skill acquisition theory defines learning as the gradual transformation of performance from controlled to automatic. This transformation happens through relevant practice over many trials, which enables controlled processes gradually to be withdrawn during performance and automatic processes to take over the same performance. The process has been called proceduralization or automatization and entails the conversion of declarative or explicit knowledge (or ‘knowledge that’) into procedural or implicit knowledge (or ‘knowledge how’). It is important to realize that the learning of skills is assumed to start with the explicit provision of relevant declarative knowledge. Thus, L2 learners (particularly instructed learners) begin with explanations explicitly presented by their teachers or in textbooks and,

An exemplary study of skill acquisition theory in SLA: DeKeyser (1997) 85

through practice, this knowledge can hopefully convert into ability for use, or implicit-procedural knowledge made up of automatic routines.

How does practice work? It helps proceduralization of new knowledge by allowing the establishment and strengthening of corresponding links in long-term memory. The more this knowledge is accessed via practice, the easier it will become to access it without effort and without the involvement of the central executive at a future time. However, the power of practice is not constant over time. There is a well-known power law of learning, by which practice will at some point yield no large returns in terms of improvement, because optimal performance has been reached (Ellis and Schmidt, 1998). In addition, proceduralization is skill-specific. Therefore, practice that focuses on L2 production should help automatize production and practice that focuses on L2 comprehension should help automatize comprehension (DeKeyser, 1997). The final outcome of the gradual process of proceduralization or automatization is automaticity, which is defined as automatic performance that draws on implicit-procedural knowledge and is reflected in fluent comprehension and production and in lower neural activation patterns (Segalowitz, 2003).

Two misinterpretations of skill acquisition tenets are common: (a) that automaticity is simply accelerated or speedy behaviour; and (b) that L2 learners simply accumulate rules that they practise until they can use them automatically. Much to the contrary, Segalowitz (2003) discusses in depth how skilled performance cannot be understood in terms of sheer speed alone, and that instead a qualitative change is reached once performance is automatized. Likewise, rather than simply accumulating rules, prolonged and repeated practice changes the knowledge representation itself by making the stored knowledge become more elaborated and well specified, or more analysed, as Canadian psychologist Ellen Bialystok (2001) has called it. This happens via processes of accretion, tuning and restructuring of knowledge (discussed by McLaughlin and Heredia, 1996; see also Chapter 6, section 6.4). In other words, by the time they become automatized, rules may be just different from the declarative rules that were initially committed to memory.

How would anyone be able to study all these abstract principles of skill acquisition theory, when it comes to L2 learning? In the next section, I will walk you through a study by DeKeyser (1997) that embodies all these principles. The study is an exemplary full-blown effort to document the time course of proceduralization during second language learning.

5.3 AN EXEMPLARY STUDY OF SKILL ACQUISITION THEORY IN SLA: