SECOND LANGUAGE LEARNING: AN INFORMATION-PROCESSING PERSPECTIVE'

Barry McLaughlin University of California, Santa Cruz

Tammi Rossman Concordia University

Beverly McLeod University of California, Santa Cruz

I t is a byword in contemporary cognitive psychology that humans are limited- capacity processors. This paper discusses ways in which children and adult learners manage to make the most of their limited processes in dealing with the complex input of a second language. An information-processing approach to second language learning is proposed and evidence in support of this approach is presented. We also discuss the implications of a n information-processing perspective for second language pedagogy and research.

This paper is a n attempt to explore the relationship between cognitive processes and the development of a second language. Without denying the validity of other points of view, we shall look a t second language learning from the perspective of human information processing. This perspective derives from contemporary cognitive psychology, with its concern for the processes of learning, perception, memory, problem solving, and decision making. It is our contention that such a n approach raises new questions that are empirically testable, and sheds light on findings from a number of areas of second language research.

HUMAN INFORMATION PROCESSING

Any communication task involves the assessment and coordination of information from a multitude of perceptual, cognitive, and social domains. The speaker must learn to obey a large number of conversational

' The authors wish to thank Mike Sharwood Smith. Ann Peters. Sacha Felix, and two anonymous reviewers for their helpful comments and criticisms of earlier drafts of this manuscript. The comments of Thomas Carr were especially helpful in writing the final version of this paper.

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conventions and must communicate the intended message unambiguously. Since humans are limited-capacity processors, such a task requires the integration of a number of different skills, each of which has been practiced and routinized. Each of these notions-that humans are limited-capacity processors, that complex skills involve the integration of elements, and that skills become routinized-requires elaboration.

Processing limitations

The limitations that exist on how individuals process information can be described along two dimensions. The first relates to the focus of attention, and is largely a function of task demands. The second relates t o information-processing ability, and is largely a function of how the individual deals with the information on the basis of past experience.

That human beings are selective in focusingattention was pointed out by William James (1890:403): “It is the taking possession by the mind, in clear and vivid form, of the one out of the seemingly several simultaneously possible objects or trains of thought.. . . ”This selectivity is required by the limited capacity of the human mind to process information. T o attend to one thing, James continued, “implies the withdrawal from some things in order to deal effectively with others”( 1890:404). Very few people can listen attentively to two simultaneous conversations.

Since James, psychologists have wrestled with the phenomenon of selective attention. Wundt ( 1896) divided mental processes into two levels-a central focus level and a peripheral diffuse level. Recent cognitive psychologists have made similar distinctions, speaking of focal attention versus preattentive processes (Neisser 1967), the selective system versus the perceptual system (Broadbent 1958), and active thought versus passive thought (Rapaport 1957). At present, cognitive psychologists tend to use a multilevel system in which, for example, attention may be divided into a central scanning process and a brief buffer storage, with connections to various memory systems such a s the sensory register, short-term memory, and long-term memory (see Blumenthal 1977). Whether this multilevel system is conceptualized in terms of specific components (e.g., Baddeley 1978) or in terms of types or levels of processing (e.g., Craik and Lockhart 1972), allowance is made for the fact that not everything reaching the organism through various input channels becomes an object of attention. Some scanning system selects one line of input over others and gives it direct access to the central cognitive system; other input sources remain on the periphery of attention. The central cognitive system can be thought of

McLaughlin. Rossman. and McLeod 137

as an executive control system (Baddeley 1981; Carr 1979) that has as its functions goal setting and task organization (Shallice 1972).

This brings us to a second dimension that relates to how individuals process information: information-processing ability. The success of the system in dealing with a given input depends on the characteristics of the input and the information-processing ability (including knowledge and expectancies) of the perceiver. If, for example, one is exposed to a rapid flow of speech in a language one does not know, the effect is that information-handling capacity becomes overloaded and one eventually “switches off.” Similarly, young children d o not attend long to speech well beyond their capacities, which is one reason why parents and othersadjust their speech in various ways when talking to young children.

In short, humans are limited-capacity information processors, both in terms of what they can attend to a t a given point in time and in terms of what they can handle on the basis of knowledge and expectations. Attention focus-what the individual can attend to a t a given point in time-can be focal or peripheral. Information-processing ability-how the individual deals with incoming information-is a function of past experience and the characteristics of the input.

Information-handling procedures: integration of elements

How is it then that individuals process large amounts of information and develop complex social, linguistic, and cognitive skills? Miller ( 1956), after all, argued that human short-term memory is limited to seven plus or minus two items. Yet Miller went on to point out that items in short-term memory are not equivalent to “bits” of information as defined by information theory. That is, items in memory can contain more than minimal amounts of information depending on the individual’s learning history and on characteristics of the input. This is well illustrated by De Groot’s research (1965) with expert chess players. These experts could almost perfectly reconstruct a chess board illustrating the chess positions of two players, even after only five seconds of exposure. This did not mean that they had better short-term memory than chess novices who could not reconstruct the board positions; they simply had more efficient ways of encoding the information into meaningful chunks. De Groot demonstrated this by showing the chess experts boards with randomized chess positions. In this case their performance was no better than chess novices.

How people chunk information has been the object of extensive research in contemporary cognitive psychology. What is a t issue here is how

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information is organized so that it can be utilized in short-term (working) memory and transferred into long-term storage. According to one approach (Craik and Lockhart 1972), there are various levels at which information can be processed, and the likelihood of long-term retention depends on the depth of processing involved. Learners use different strategies to handle input, some of which involve "deeper" levels of processing and result in superior long-term retention. While this approach is vulnerable to criticism on empirical grounds (Baddeley 1978), the levels- of-processing framework is helpful in that it suggests that poor learners may not suffer from inherent storage or capacity deficits, but rather need to apply different learning strategies.

The organization of long-term memory systems is another factor that affects the manner in which information will be handled. Cognitive psychologists differ as to whether they regard the long-term memory system as being organized in terms of associative networks or hierarchical systems (see Ander son a n d Bower 1974). In e i ther case, the predetermination of relations between elements reduces the amount of cognitive effort required t o handle isolated bits of information. By dealing with related units of information rather than isolated bits, more efficient processing becomes possible.

In recent years researchers have investigated the effects of practice, rehearsal, and familiarity on information processing. A particularly important variable appears to be the degree of attention involved. The more attention required, the more resources are consumed and the slower the processing. Greater practice, rehearsal, or familiarity with the material allows information to be handled more routinely without as much cost in attentional monitoring as when there is less practice, rehearsal, or familiarity with the material.

The routinization of skills: controlled and automatic processes

I f we assume that some tasks consume more resources and involve slower processing than others, on what basis is processing energy allocated? Kahneman ( 1973) has suggested that the amount of processing energy consumed depends on the nature of the task; certain mental operations require greater processing capacity than others.

Several researchers (LaBerge and Samuels 1974; Schneider and Shiffrin 1977; Shiffrin and Schneider 1977) have conceived of the differences in the

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processing capacity necessary for various mental operations in a dichotomous way: Either a task requires a relatively large amount of processing capacity, or i t proceeds automatically and demands little processing energy. Furthermore, a task that once taxed processing capacity may become so automatic that it demands relatively little processing energy.

In their discussion of human information processing, Shiffrin and Schneider conceived of memory a s a large collection of nodes that become “complexly interassociated” through learning. Each node is a grouping or set of informational elements. Most of the nodes are inactive and passive and, when in this state, the interconnected system of nodes is called long- term store (LTS). When, because of some kind of external stimulus, a small number of these nodes a re activated, the activated nodes constitute short- term store (STS).

There are two ways in which these nodes become activated: Shiffrin and Schneider called these the automatic and the controlled modes of information processing. Automatic processing involves the activation of certain nodes in memory every time the appropriate inputs are present. This activation is a learned response that has been built up through the consistent mapping of the same input to the same pattern of activation over many trials. Since a n automatic process utilizes a relatively permanent set of associative connections in LTS, most automatic processes require an appreciable amount of training to develop fully. Once learned, an automatic process occurs rapidly and is difficult to suppress or alter.

The second mode of information processing, controlled processing, is not a learned response, but a temporary activation of nodes in a sequence. This activation is under attentional control of the subject and, since attention is required, only one such sequence can normally be controlled at a time without interference. Controlled processes necessarily intrude on the ability to perform simultaneously any other task that also requires a capacity investment. Controlled processes are thus tightly capacity- limited, and require more time for their activation. But controlled processes have the advantage of being relatively easy to set up, alter, and apply to novel situations.

Two aspects of this conceptualization of information processing are especially important for the present discussion. First, learning involves the transfer of information t o long-term memory and is regulated by controlled processes. That is, complex skills are learned and routinized (i.e., become automatic) only after the earlier use of controlled processes. It

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is controlled processes that regulate the flow of information from working to long-term memory. Learning involves time, but once automatic processes are set up at one stage in the development of a complex information-processing skill, controlled processes are free to be allocated to higher levels of processing. Thus controlled processing can be said to lay down the “stepping stones” for automatic processing as the learner moves to more and more difficult levels (Shiffrin and Schneider 1977).

Second, the distinction between controlled and automatic processing is not based on conscious experience. Both controlled and automatic processes can in principle be either conscious or not. Since most automatic processes occur with great speed, their constituent elements are usually, but not necessarily, hidden from conscious perception. Some controlled processes also occur with great speed, so that they may not be available to conscious experience. Shiffrin and Schneider ( 1977) called these controlled processes “veiled.” Other controlled processes, those they referred to as “accessible,” are easily perceived by the learner.

This complexity is illustrated in Table I . Controlled processes may occur with or without awareness, depending on the learner’s focus of attention. While some attention is needed for all controlled processes, certain new skills-e.g., learning to drive a car-may require that the learner focus attention on the various component skills involved (Cell A). Other skills- e.g., learning to speak grammatically in a first language-may involve only peripheral attention (Cell C). Thus children learn the rules of grammar “incidentally” as a byproduct of trying to communicate with others. Automatic processes can also become the focus of attention, when one deliberately attends to a skill one normally performs routinely-e.g., driving or typing (Cell B). Most automatic processes, however, are performed without deliberate awareness-e.g., adults speaking their first language-so that attention is freed for other tasks (Cell D). In Table 1 , the “intentional”-“incidental” distinction refers to the extent to which task demands on a particular occasion require focal or peripheral attention (McLaughlin 1965), recognizing, of course, that there are shades of gray at the point where focal and peripheral attention converge.

In short, the controlled process-automatic process distinction is not based on conscious versus subconscious awareness, but instead relates to the degree to which the skills in question have been routinized and established in long-term memory. To the extent that this has not occurred, information-processing techniques can be said to be imperfectly mastered, temporary, and subject to controlled processing; to the extent that the skills

McLaughlin. Rossman, and McLeod 141

Table I Per/ormanc e UJ a /uric tion of information processing and fooc UJ of attention

Focus of Information processing attention Controlled Auiomatic

(Cell A) (Cell B) Focal “Intentional” performance “Intentional” performance

of a new skill of a well-trained skill

(Cell C) (Cell D) Peripheral “Incidental” performance “Incidental” performance

of a new skill of a well-trained skill

are well-mastered and permanent, information processing can be said to be automatic. Optimal performance requires a flexible blend of automatic and controlled processing (Bock 1982; Shallice 1972). Routine activities must be automatized so that resources are available for higher-order processing, but a t the same time, failure to employ controlled processes can lead to rigidity and sterile performance.

INFORMATION PROCESSING AND SECOND LANGUAGE LEARNING

I t is currently popular in discussions of second language learning to distinguish between two processes: learning and acquisition. This distinction has been made by a number of people, but is principally associated with Krashen’s Moni to r Model of second language performance (Krashen 1976, 1977). As Krashen and others use it, the learning/ acquisition distinction is based on whether the processes involved are “conscious” (as in learning) or “subconscious” (as in acquisition). As Krashen noted, “special experimental conditions are necessary”( 1979: 152) to validate such a distinction. Yet no such procedures exist. Krashen’s attempt to have subjects distinguish whether they are operating by “rule”or “feel” (Krashen, Butler, Birnbaum, and Robertson 1978) is woefully inadequate (McLaughlin 1978). and arguments as to whether particular construct ions a re acquired o r learned (Krashen 1979: 152-153; McLaughlin 1978:317-3 18) merely underscore the difficulty of operating on the basis of “conscious” experience. Introspection and subjective reports are notoriously unreliable and easily mistaken. The windows to our minds are unfortunately rather clouded (Shatz 1977).

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Controlled and automatic processes in second language learning

Because the learningiacquisition distinction is so difficult to pin down, we believe that the pie should be cut in a different way. Instead of making a distinction between learning and acquisition that rests on whether the processes are conscious or subconscious, we propose that the distinction between controlled and automatic processes be used to differentiate processes that are capacity-limited and temporary and those that are relatively permanent and nearly always become active in response to a particular input configuration. As we have just seen, controlled and automatic processes can be either the focus of attention (which is usually, but not always, true of controlled processes) or on the periphery of attention (which is usually, but not always, true of automatic processes). Since, however, controlled and automatic processes may or may not be subject to conscious awareness, the distinction cannot be equated with Krashen’s learning/ acquisition distinction (McLaughlin 1978).

In an information-processing perspective, learning in the initial stages is seen to involve the use of controlled processes with focal attention to task demands. As the learner becomes more familiar with the situation, attention demands are eased and automatic processes develop, allowing other controlled operations to be carried out in parallel with automatic processes as performance improves. In second language learning, for example, the initial stages of learning involve the slow development of skills as the learner attempts to automatize the various components of performance.

Does this mean that second language learning inevitably involves the initial assimilation of rules that are then applied with focalattention to task demands? This is one strategy, but there are others depending on how the individual approaches the task of learning a second language and what the demand characteristics of the situation are. Table 2 outlines some possibilities. A learner may, for example, initially focus attention on formal rules (Cell A), but this attention to formal properties can also be peripheral (Cell C ) . In the second case, learning may take the form of “implicit learning,” which involves the relatively passive apprehension of linguistic structure and a focus on other (e.g., communicative) task demands, or “analogic learning,” whereby learners generalize around instances and build up their knowledge of formal linguistic structure from instances rather than from formal rules (see McLaughlin 1980a). Once

McLaughlin, Rossman. and McLeod 143

learning is routinized, information processing is automatic and may involve attention to formal properties-as in a test situation (Cell B)-or may not involve such attention-as in normal communication in natural settings (Cell D).

Table 2 Possible second language performan1.e as a,func,rion ofin/ormarion-processinl: procedures

and arrenrion rojormal properries v/ language

Attention to formal properties Information processing of language Controlled Automatic

Focal (Cell A )

Performance based on formal rule learning

(Cell B) Performance in a

test situation

(Cell C) (Cell D) Performance based Performance in

Peripheral on implicit learning communication or analogic learning situations

It is important to recall that the attentional dimension is viewed as a continuum, with sufficient allowance for the fact that in many instances it is difficult to know exactly how attentive the learner is t o formal linguistic properties. There are also many gradations along the controlled-automatic axis, with native language processing at the automaticend and a beginning second language learner a t the controlled end of the continuum.

Another example might be helpful for understanding Table 2. One might deliberately eavesdrop on a conversation in a language that one knows imperfectly (Cell A). Understanding the content of the conversation in such a case would differ from unintentionally overhearing a conversation in that language, where the person might not be fully aware of overhearing and understanding something until afterwards (Cell C ) . Similarly, one might eavesdrop on a conversation in one’s native language (Cell B), and this would be different from unintentionally overhearing a conversation in that language (Cell D).

Workload requirements in second language learning

At this point it is useful to summarize the basic assumptions of the approach we are taking to second language learning. First, it is assumed that humans are limitedcapacity information processors. As we saw

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earlier, this limitation reflects restrictions on what can be attended to a t a given point in time, and on how information is processed in terms of an individual’s knowledge and expectations. Second, it is assumed that in order t o function effectively, humans develop ways of organizing information. Some tasks require more attention; others that have been well-practiced require less. The development of any complex skill involves building up a set of well-learned, automatic procedures so that controlled processes will be freed up for new tasks. In this way limited resources can be spread thinly to cover a wide range of task demands.

In this conceptualization, complex tasks are characterized by a hierarchical structure. That is, such tasks consist of subtasks and their components. The execution of one part of the task requires the completion of various smaller components. The various subroutines may, however, be learned independently. People usually try to learn the various subtasks more o r less concurrently. That is, the attention given to various subroutines is typically on a time-shared basis, with the learner attending now to one feature and then to another. But eventually the subroutines need to be integrated to attain the higher-order goal.

Levelt (1977) maintained that speaking is an excellent example of a hierarchical task structure. The first-order goal is to express a particular intention. T o d o this, the speaker must decide on a topic and select a certain syntactic schema. In turn, the realization of this schema requires subactivities, such as formulating a series of phrases to express different aspects of the intention. But to utter the phrases there is need for lexical choice, activation of articulatory patterns, utilization of appropriate syntactic rules, etc. Whether the process is strictly hierarchical is open to debate, since there may be an interaction between the various subactivities, with, for example, lexical decisions influencing syntactic choice (Bock 1982). Nonetheless, each of the component skills needs to be executed before the higher-order goal can be realized.

To attain the higher-order goal the learner needs a plan, whereby the selection of subactivities is regulated according to overriding goals. The plan controls the order in which a sequence of operations is to be performed (Lichtenstein and Brewer 1980). Plans include goal states, procedures for reaching the goal state from any initial state, and tests for evaluating if the goal state has been or will be reached (Miller, Galanter, and Pribram 1960). An automated plan can consist of lower-level components that may or may not be automated and whose selection is governed by the master plan. Levelt (1977) pointed out that the choice o f a particular lexical entry during the execution of an automatic phrase-

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building plan may depend on the choice of particular words in an earlier phrase, on the topic of discussion, and so on. Consequently, even for native speakers, lexical decision may require substantial attention (see Bock 1982).

In the case of a beginning second language learner a considerable amount of cognitive effort may be needed simply to realize a correct, or a t least an adequate, phonetic expression of individual words. At the same time, the learner needs to employ appropriate syntactic rules and must draw on a limited lexical system. Thus each component requires more or less work depending on how well-learned it is. The more well-learned a component skill is, the less effort (and processing time) required for its execution. The execution of new skills is costly in terms of workload involved and will occur only when other tasks and cognitive demands are minimized.

Tarone (1979) has argued that data gathered in informal settings reveal the most systematic interlanguage style and the style least subject to interference. The informal, or “vernacular,” speech style is a product of language skills that are relatively more automatic (Tarone 1982). When the learner directs attention to speech, controlled processes come into play and performance is likely to be interfered with-just as driving or typing are likely to be interfered with (or a t least slowed down) when theseautomatic skills are given too much attention. When skills are not completely automatized, however, performance can be improved by giving the learner more time to apply controlled processes. Thus learners in test situations sometimes d o better when given more time because the test items are not automatized and require the application of controlled processes.

Another factor affecting workload requirements is the complexity of the task. Initially, of course, the second language learner is confronted with a “blooming, buzzing confusion.” The tendency in this situation is to fall back on old skills, to use one’s first language to crack the code of the second. For example, the learner at this stage may execute those routinized operations that are normally designed to produce utterances in the first language, although attempting to employ the sound system and lexicon of the second language. At some intermediate stage, target language routines may become more automatic, thereby lessening cognitive demands. As workload requirements lessen, there should be less reliance on old skills, which is in accord with the finding that interference errors predominate early in learning (Taylor 1975) or when learners confront intractable problems that impose significant new cognitive demands (Wode 1978).

Note that in thisaccount of the second language learning process, what is

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learned does not consistently display itself in performance. Situational demands and the cognitive demands of the task itself affect the likelihood that new skills will be revealed. Interference errors and deviations from systematic developmental patterns are seen as evidence that new skills are inhibited because of excessive workload demands. Only when the cognitive workload is reduced does one get a veridical picture of what has been learned.

Most adult second language learners are familiar with the experience described by Brown (1973) of knowing words, phrases, and sentences in a second language perfectly for classroom use, but being unable to utilize them outside of the classroom when in contact with native speakers of the target language. One explanation of this phenomenon is tha t the individual’s full range of linguistic abilities is not displayed because the workload involved in maintaining conversational interaction has overloaded information handling capacities. Thus individuals such as Krashen’s “P” (see Krashen 1979), who display accurate knowledge of formal rules but d o not use them in conversational speech, cannot handle a t one time the two competing demands of maintaining the flow of conversation and speaking accurately in a formal sense.

In addition, person variables interact with task and situation demands, as can be illustrated through one of psychology’s classic principles, the Yerkes-Dodson law (1908). According to this law, performance on any task is a n inverted U function of motivation level. As motivation increases, performance increases-up to a point. Beyond this point, performance decrements are incurred a s increasing levels of motivation, accompanied by increasing arousal and anxiety, disrupt performance. For example, some motivation is beneficial t o performance on a n examination, but too much disrupts performance. Figure 1 illustrates how individuals differ in their tolerance for higher motivation levels. Some people (e.g., B) perform best under motivation conditions (e.g., point X) that seriously impair the performance of other individuals (e.g., A).

This picture is complicated by the fact that different tasks have different optimal levels of motivation. This can be seen in Figure 1 if curve A is thought t o represent a task with high information-processing demands and curve B a task with low information-processing demands. Lower levels of motivation disrupt performance on the complex task: At point X, performance on task A is disrupted, whereas this level of motivation produces optimal performance on the less complicated task B.

Although the Yerkes-Dodson law was expressed in terms of levels of motivation, it could be expressed equally well in terms of information-

McLaughiin, Rossman. and McLeod 147

High

Low

\ \ \

B

1.ow Point X

High

Motivational level

Figure 1. The Yerkes-Dodson law (1908). There is an optimal degree of motivation for performance on a task, after which point further increases in motivation disrupt performance. Individuals (andtasks)diffPr in the levelof motivation neededfor optimal performance.

processing workload requirements (Kahneman 1973; Levelt 1977). Individuals differ in the amount of information they can process a t any one time; what constitutes a n overload (i.e., degrades performance) for individual A may provide the ideal cognitive demands for individual B. Similarly, different tasks and situations involve different information- processing workload requirements; an equal cognitive effort can produce very different results in two distinct situations. Note, however, that these variables never operate in isolation in the real world. Individual differences interact with situational factors in a complex manner (McLaughlin 1980b).

PROCESSING A SECOND LANGUAGE: SOME RESEARCH FINDINGS

For some time now, experimental psychologists have approached language as linguistic information that must be processed in order to be understood. There has been relatively little research on either first or second language learning from this conceptual point of view. There are, however, some relevant studies. In this section we refer to some research results that bear upon the approach to second language learning we advocate in this paper.

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Automaticity in lexical retrieval

Much recent psycholinguistic research has focused on the relevance of the automatic-controlled dichotomy to the manner in which the strength of association between a word and its meaning is established (e.g., Posner and Snyder 1975). One experimental paradigm is the lexical decision task, in which subjects are required to make a decision about a target stimulus (e.g.. oak) for which they have been given a prime signal that is either semantically related to the target stimulus (e.g., e h ) or not (e.g., truck). Favreau (198 1 ) used this paradigm to investigate the extent to which there is a semantic facilitation effect (i.e., where a prime that is semantically related to a target word will increase the speed with which the target word is processed) for both balanced bilinguals and dominant bilinguals highly skilled in their second language. Subjects were shown a prime that was either semantically related or unrelated to the target. The target sometimes was a word and sometimes a nonsense syllable. The time between the showing of the prime and the target was manipulated and the subjects'task was t o decide as rapidly as possible whether the target formed a word.

Favreau found that both balanced and dominant bilinguals showed evidence of semantic facilitation in their first language and in the long time interval condition in their second language, but only balanced bilinguals showed the same semantic facilitation in the short time interval condition in their second language. This was interpreted as evidence that the dominant bilinguals, who were judged to be fluent in their second language, nonetheless d o not process lexical items as efficiently as balanced bilinguals. This lesser efficiency in automatized lexical processing was thought to be the reason why the dominant bilinguals were found to read more slowly in their second than in their first language, while this was not the case for the balanced bilinguals.

More proficient second language learners also differ from less proficient learners in that they use different techniques for encoding lexical items in memory. Henning (1974) found that adult second language learners made more or less use of acoustic encoding in a vocabulary recognition task as a function of their degree of proficiency in the second language. More advanced learners and native speakers tended to make errors that indicated semantic clustering for lexical items, whereas less advanced learners showed evidence of a predominance of acoustic clustering rather than semantic clustering. In our terms, the less advanced learners have not yet automatized formal-in this case acoustic and orthographic-aspects of

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the language, and so have less cognitive energy available for semantic avpects. More advanced learners have automatized the acoustic and orthographic aspects of the task, having already achieved automaticity with respect to these subcomponents.

Dornic (1979) reviewed a series of studies dealing with automaticity of processing in bilingual subjects. Using speed of processing as a measure of automaticity, Dornic found that speed increases as a function of experience with language. This was true with respect to both decoding and encoding efficiency. Typically, the semantic content of words tended to be decoded more slowly in the second language, and the subjects’ ability to encode information in the second language (as measured by naming latencies) tended to be inferior to performance in the first language. Presumably the second language had not attained the degree of automaticity that characterizes the first, even in the case of subjects who are overtly balanced bilinguals.

In a cross-sectional study of 13- to 18-year-old German-Swedish bilinguals, Magiste (1979) found that it took a somewhat shorter time to develop proficiency in the decoding than in the encoding process of a second language. In her research, reaction time measures to verbal stimuli were used to assess both decoding and encoding ability. Monolingual subjects had faster reaction times, especially in encoding tasks, than did bilingual subjects in their second language, leading Magiste to hypothesize that the poorer performance of bilinguals is due to their failure to achieve the same levels of automatic familiarity with the words of their second language as monolingual subjects achieve.

Dornic (1979) reported that high information load enhances the dominance of the bilingual’s stronger language system. Noise and other stressors interfere significantly with the weaker language, speech in that language becoming slowed down, rendered less precise, or even entirely blocked. In the terminology of our earlier discussion, the workload requirements degrade performance in the second language when cognitive and situational demands are increased beyond some optimal point.

Automaticity in syntactic processing

Hatch, Polin, and Part (1970) asked university-level native and nonnative speakers to cross out all of the instances of certain letters (e.g., all e’s) occurring in a text. They reported that nonnative speakers found the instances of occurrence of the letters with equal frequency in both content

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and function words, but that native speakers ignored the letters more often in the function words than in the content words. This phenomenon can be explained in terms of the amount of cognitive work required by the nonnative speaker to process the language. Nonnative speakers expended equal cognitive effort in processing both syntactic (as represented by the function words) and semantic (as represented by the content words) aspects of language. Native speakers, on the other hand, more frequently missed the target letters found in function words, suggesting that they generally did not focus their attention on such words. Instead, native speakers focus their attention on meaning (on content words), processing syntactic elements automatically when scanning a text.

Psycholinguistic evidence for differential processing of semantics and syntax by native speakers comes from Sachs’ classic finding (1967) that recognition memory for semantic features of an utterance was superior to recognition memory for syntax. Rossman (198 1) hypothesized that this would not be the case for nonnative speakers, who have not yet achieved the degree of automaticity in processing syntax that characterizes native speakers. Rossman compared the performance of native speakers with two groups of nonnative speakers of English on a reading recognition test. Native speakers showed better recognition for semantic than for syntactic changes. Nonnative speakers, however, showed a greater ability to recognize whether the form of the sentence was changed than to recognize that its meaning was altered.

In a similar study, Wolfe (198 I ) tested 55 English-speaking children learning French as a second language in California schools. The children read a paragraph and were then shown a target sentence that they were to identify as “the same” or “different” from a sentence in the paragraph. The paragraphs were either entirely in English or entirely in French or mixed with sentences in both languages. The target sentences were either in the same or in a different language and had either the same or a different meaning. Children who were more proficient in the second language recognized more changes in meaning correctly, but made more errors in recognizing changes in the language of the sentence than did less proficient children. This suggests that the more proficient children had achieved a degree of automaticity with respect t o processing form (in this case the specific language of the sentence) that the less proficient children had not yet attained.

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Automaticity in reading

One aspect of second language performance where the automatic/con- trolled processing distinction is especially relevant is reading. Shiffrin and Schneider ( 1977) argued that in learning to read, children utilize controlled processing to lay down “stepping stones” of automatic processing as they move on to more and more difficult levels of learning. The transition from controlled to automatic processing at each stage results in reduced discrimination time, more attention to higher-order features, and ignoring of irrelevant information.

If the reading process can be viewed as a sequence of transitions from controlled to automatic processing, one would expect second language learners to differ from native speakers in processing text. Cziko (1980) compared French oral reading errors of two groups of seventh grade English-speaking students with those committed by native French- speaking students. Students of intermediate proficiency in French made a significantly higher proportion of substitution errors that graphically resembled the text than did advanced second language speakers or native speakers. Moreover, the intermediate group also made a significantly lower proportion of deletion and insertion errors than did the other two groups. That is, the least proficient group, when reading a sentence such as She shook the piggy bank and out came some money, would be likely to substitute many for money (relying on graphic information), whereas more advanced second language learners and native speakers were more likely to insert dimes or dollars for money (relying on contextual and semantic information). This lends support to the notion that a sequence of stages is involved in the reading process and that less proficient second language learners have not yet automatized skills as more advanced learners have.

Cummins (198 1) has suggested that the development of linguistic skills be conceptualized as a continuum, with some skills requiring more and some less active cognitive involvement. ‘Those tasks for which the linguistic tools have become largely automatized (mastered) require little cognitive involvement for appropriate performance. Those tasks where this is not the case require a greater cognitive involvement. In reading, word decoding skills are the first that require cognitive involvement. As the learner progresses, a degree of automaticity is achieved with respect to word decoding, and this process can be short-circuited as the learner engages in the process of sampling from the text to confirm predictions.

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Much of the difficulty that children in bilingual programs experience in learning to read can be viewed as a failure to automatize lower-level skills that are needed in the reading process. Children who learn to read in a second language must use a new vocabulary and syntactic system to make predictions about the text. The disharmony created by failure to predict slows the reader t o a painful process of word-by-word decoding (Kaminsky 1976). with attendant discouragement.

IMPLICATIONS FOR SECOND LANGUAGE PEDAGOGY AND RESEARCH

An information-processing approach stresses the limited cognitive capacities of human learners, the use of various information-handling techniques to overcome these limitations, and the integration of subskills in mastering complex skills. The acquisition of a complex skill, such as learning a second language, is thought to involve the gradual integration of lower-level skills and their accumulation as automatic processes in long- term storage. In the learning process component skills that require more mental work become routinized and thereby free up controlled processes for other functions. As automaticity develops, controlled processing is bypassed and attentional limitations are overcome. This transition from controlled to automatic processing is central to learning.

But how is this transition achieved? There are a number of ways of describing the language learning process from an information-processing perspective. One way is through what is fashionably known in thejargon of cognitive psychology as fop-down information processing; another is through boffom-up information processing. The terms derive from the field of artificial intelligence and are used in a number of different senses. In one meaning, a topdown, or knowledge-driven, system is thought to use higher-level information to facilitate processing of incoming data. A bottom-up, or inductive, system relies principally on the information carried by the input. A t opdown, or deductive, system uses information from wider contexts (higher-level knowledge). From our point of view, both bottom-up and t o p d o w n processing are subtypes of controlled processing directed at achieving automaticity.

Speech to young children tends to be concrete and limited to events in the immediate perceptual field (Hatch 1978). Data-driven, bottom-up processing is adequate to deal with such relatively clear input and children usually d o not seek out abstract, higher-level information about language.

M c Laughlin. Rossman. and M c Leod 1.53

The best pedagogical results are likely to come from instruction that prmides input within the child’s range of acceptance (i.e., input that is neither so easy nor so difficult that the child “switches off‘-see Krashen 1980). One way to d o this is by focusing on tasks that require meaningful communication.

Ordinary speech to adults, on the other hand, tends to be more abstract and therefore more difficult than that which children hear. In this case, interactive bottom-up and top-down processing is likely to produce the best pedagogical results. That is, some higher-level abstract knowledge of linguistic structure is likely to help adult learners process a second language. Indeed, Seliger (1975) found that adult learners given prior knowledge of a rule system for the English article displayed greater long- term gains in mastering the article than subjects lacking this knowledge. Furthermore, abstract knowledge of rule systems may serve second language learners as a shortcut in the learning process, saving them from the trouble of generating false hypotheses about underlying rules.

By this we d o not mean to advocate any one particular teaching method. As we argued earlier, there are a number of strategies learners can use in tackling a second language, depending on the degree of focal attention given to formal rules. The success of any particular strategy depends on the characteristics of the situation and on individual learning styles. When the input is relatively clear, an “implicit 1earning”strategy (McLaughlin 1980a) might be most successful. That is, the learner might d o best to ignore explicit considerations of form, and focus instead on communication. By keeping the input clear (i.e., not too much in advance of learnercapacities) and by concentrating on the kinds of “meaningful” and “communicative” drills advocated by Krashen (1980), the teacher might produce the best results, even with adult learners. Individual learning styles enter in here, however. Some adult learners have a greater need than others to work from knowledge of the rules-Hatch (1974) called such individuals “rule learners.” Others prefer to work from the input-Hatch’s “data gatherers.” Optimizing outcomes involves fitting the instruction treatment to the individual’s learning style-which is the ultimate practical goal of research on second language development (McLaughlin 1980b).

It is often thought that an approach that focuses on the integration of skills invariably stresses routine drills. It is true that in our conception of the language learning process, repeated performance of the components of the task through controlled processing leads to the availability of automatized routines. As was mentioned earlier, however, these

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automatized routines should be conceptualized as higher-order plans. Such plans are thought t o be flexible entities that allow for integrated execution of various complex tasks. As Levelt (1977) noted, while an essential object of training is automatization of lower-level components, i t is incorrect to conclude that this should be done exclusively by frequent repetition of one and the same activity. Training should involve the frequent use of a particular sentence structure in varied lexical settings, not in the frequent use of particular sentences (Levelt 1977; McLaughlin 1979). Once automaticity is developed and controlled processing bypassed, the learner should be able to call up different lexical items and different syntactic subcomponents, depending on the task. Thus the same plan can generate different realizations depending on the lexical setting.

To summarize, the information-processing perspective does not offer prescriptive guidelines to the hard-pressed second language instructor. At this stage, we d o not see our approach as providing much definitive advice to second language pedagogy. Instead, we believe the information- processing perspective provides a valuable research point of view. By using objective measures developed by cognitive psychologists to measure information processing, researchers interested in the second language learning process can determine whether individuals or groups are processing language in different ways,

The hallmarks of automatic processing a re increased speed and reallocated attention. These are empirically testable phenomena. Dornic’s research (1979) is a good example of how reaction time measures can be used to determine efficiency in processing linguistic material in first and second languages. Dornic’s research also indicated that under conditions where workload requirements were increased, attention was shifted from the less dominant language so that performance in that language, but not in the more dominant language, deteriorated.

In addition to reaction time measures, there are other objective means of assessing information processing in second language learners. In Favreau’s study ( 198 I ) , the presence of semantic facilitation with short intervals between prime and target words indicated highly efficient (automatic) processing, whereas its absence indicated less efficient processing. Another procedure is the Stroop task, in which subjects are shown color words written in incongruent ink colors and are asked to name the color in which the word has been written. Presenting this task to bilingual subjects yields information about the degree of automaticity of lexical retrieval in the two languages, since the inability to inhibit an interfering process strongly

McLAaughlin, Rossman, and McLeod 1.5.5

indicates that the lexical retrieval process is a n automatic one (Posner and Snyder 1975). Another paradigm involves ambiguous words. Monolingual subjects have been shown to be able to process the multiple meanings of ambiguous words even when the context is compatible with only one meaning (e.g., Conrad 1974), which suggests that meaning activation is automatic in such subjects. The same paradigm could be used to investigate the degree to which meaning activation is (or is not) automatic in second language learners with differing degrees of proficiency in a particular target language. Finally, analysis of the sources of errors in sentence production can provide information about the conditions under which the automatic operations that support sentence formulation fail (Bock 1982).

A long-term goal for research on second language learning from an information-processing perspective is a “components skills analysis”(Carr 1981). The first step in such an analysis is to specify the component information-processing skills that make up the task of learning a second language, the second is t o determine which specified skills potentially are involved in determining individual variation in overall success on the task, and the third step is to determine the relative contribution to variation in overall success that is in fact made by each skill or skill group. Carr’s analysis (198 1 ) of the reading process is a helpful model, but research on second language learning has not achieved the sort of experimental sophistication that has been attained in research on reading.

In this paper we have focused primarily on one aspect of information processing-the role of automaticity in second language learning. We have not elaborated other aspects of this approach, such as the focus of attention dimension or the role of the executive control system. An adequate information-processing theory of second language learning would include not only specification of how automatic and controlled processes are coordinated, but would also require an understanding of selective attention and the role and function of consciousness. For example, such a theory would have to be able to account for how second language learning occurs with “peripheral” as opposed to “focal” attention to the formal properties of language (e.g., “implicit learning”-see McLaughlin 1980a).

We d o not mean to imply that an information-processing approach to second language learning is a complete one. Such a perspective is only one way of looking at language learning. In this respect we agree with Lakoff and Johnson (1980) that “truth” is always relative to a conceptual system defined in large part by metaphQr. There is no single absolute truth about second language learning; we are all like the blind Indians describing an

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elephant. Our approach has certain advantages for research purposes, but it does not say much, for example, about why certain formal aspects of language are more difficult for certain learners to acquire than are other structures. For this we turn to the linguist. On other issues one must consult developmental psychologists or educators. Second language learning is a complex phenomenon and there are many legitimate points of view. The trouble begins when one starts to claim that a particular point of view is the total one.

REFERENCES

Anderson, J.R.. and G.H. Bower. 1974. Human Associative Memory. New York: Wiley. Baddeley. A.D. 1978. The trouble with levels: a reexamination of Crdik and Lockhart's

Baddeley, A.D. 1981. The concept of working memory: a view of its current state and

Blumenthal. A.L. 1977. The Process of Cognition. Englewood Cliffs. N.J.: Prentice-Hall. Bock. J . K . 1982. Toward a cognitive psychology of syntax: information processing

Broadbent. D. 1958. Percepprion and Communication. New York: Pergamon. Brown, R. 1973. Development of the first language of the human species. Amerkan

Carr. T.H. 1979. Consciousness in models of human information processing: primary memory. executive control and input regulation. In Aspwts q / Consciousness. Vol. I . Ps.vc,hological Issues. ed. G. Underwood and R. Stevens. London: Academic Press.

Carr. T.H. 1981. Building theories of reading ability: on the relation between individual differences in cognitive skills and reading comprehension. Cognition 9:73-1 14.

Conrad. C. 1974. Context effects in sentence comprehension: a study of the subjective lexicon. Mernor.v and Cognition 2: 130-1 38.

Craik. F.I.M.. and R.S. Lockhart. 1972. Levels of processing: a framework for memory research. Journal of Verbal Language and Verbal Behavior I 1:671-684.

Cummins, J. 1981. The role of primary language development in promoting educational success for language minority students. In Schooling and Language Minoripry Srudenrs: A Theoretical Framewmork. Los Angeles: Evaluation. Dissemination and Assessment Center. California State University.

Cziko. G.A. 1980. Language competence and reading strategies: a comparison of first- and second-language oral reading errors. Language burning 30: 101-1 16.

De Groot. A.D. 1965. Thought and Choice in Chess. The Hague: Mouton. Dornic. S. 1979. Information processing in bilinguals: some selected issues. PsycholoRical

Research 40: 329-348. Favreau. M. 1981. Automatic and Conscious Attentional Processes in First and Second

Languages of Fluent Bilinguals: Implications for Reading. Doctoral dissertation, Concordia University.

Hasher. L.. and R.T. Zacks. 1979. Automatic and effortful processes in memory. Journal(/ Experimental Ps.vcholog.r.. General 108:356-388.

Hatch, E. 1974. Second language acquisition ~ universals'? Working Papers on Bilingualism 3:l-17.

framework for memory research. Psychological Review 85: 139-1 52.

probable future development. Cognition 10: 17-23.

contributions to sentence formation. Ps.vchologii,al Review 89: 1-47,

Psychologist 28:97-106.

Mc Laughlin, Rossman, and Mc, Leod 15 7

Hatch, E. 1978. Discourse analysis and second language acquisition. In Swond Language

Hatch. E.. P. Polin. and S . Part. 1970. Acoustic Scanning or Syntactic Processing. Paper

Henning. G. H . 1974. Remembering foreign language vocabulary: acoustic and semantic

James. W. 1890. The Princ,iples ?/ f.vycholog.r.. New York: Holt. Kahneman, D. 1973. Arrention and EJort. Englewood Cliffs. N.J.: Prentice-Hall. Kaminsky. S. 1976. Bilingualism and learning to read. In The Bilingual Child. ed. A. Simoes.

New York: Academic Press. Krashen. S . 1976. Second Lmguage Acquisiiion. Survqv of Linguistic Science, ed. W .

Dingwall. Stamford. Conn. Greylock. Krashen. S. 1977. The Monitor Model for adult second language performance. In Vienpoints

on English as a Second Language, ed. M. Burt. H. Dulay, and M. Finocchiaro. New York: Regents.

Krashen. S. 1979. A response to McLaughlin. “The Monitor Model: Some methodological considerations.” Language Learning 29: 15 1-167.

Krashen. S. 1980. Relating theory and practice in adult second language acquisition. I n Sewnd Language Development. ed. S . Felix. Tuebingen: Narr.

Krashen. S.. J . Butler, R. Birnbaum and J . Robertson. 1978. Two studies in language acquisition and language learning. ITL: Review, of Applied Linguistics 3940.

LaBerge, D.. and S.J. Samuels. 1974. Towards a theory of automatic information processing in reading. Cognitive fs,rchology 6:293-323.

Lakoff. G. . and M. Johnson. 1980. Metaphors we live by. Chicago: University of Chicago Press.

Levelt. W.J.M. 1977. Skill theory and language teaching. Studies in Sewnd Language Aquisirion I :53-70.

Lichtenstein, E.H., and W.F. Brewer. 1980. Memory for goaldirected events. Cognriive Psychology 12:412445.

Magiste. E. 1979. The competing language systems of the multilingual: a developmental study of decoding and encoding processes. Journal of Verbal burning and Verbal Behavior I8 :79-90.

McLaughlin. B. 1965. “1ntentional”and “incidental”learning under conditions of intention to learn and motivation. Psr,vhologicd Bulletin 63:359-376.

McLaughlin, B. 1978. The Monitor Model: some methodological considerations. Language burning 28:309-332.

McLaughlin. B. 1979. Linguistic input and conversational strategies in L I and L2. Studies in Sewnd Language Acyuisrrion 2: I - I 6

McLaughlin, B. 198Oa. On the use of miniature artificial languages in second-language research. Applied fsyc~holinguisrics 1:357-369.

McLaughlin, B. 1980b. Theory and research in second-language learning: an emerging paradigm. Language burn ing 30:331-350.

Miller. G.A. 1956. The magic number seven. plus or minus two: some limits on our capacity for processing information. fs.r.c.hologic,al Review 63:8 1-97.

Miller. G.A., E. Galanter, and K . Pribram. 1960. Plans and rhe Structure vf6ehuvior. New York: Holt. Rinehart. & Winston.

Neisser. U. 1967. Cognitive Psjschology. New York: Appleton-Century-Crofts. Posner. M.I.. and C.R.R. Snyder. 1975. Attention and cognitive control. In lnjormation

Processing and Cognition: The Lqyola Symposium, ed. R.L. Solso. Hillsdale. N.J.: Erlbaum.

Arquisition. ed. E. Hatch. Rowley, Mass : Newbury House.

presented at meeting of the Western Psychological Association, San Francisco.

parameters. Language Learning 23: 185-196.

Rapaport. D.. ed. 1957. Cognirive Srrui,rures: Collected Papers. New York: Basic Books.

158 Language Learning Vol. 33* N o . 2

Rossman. T. 1981. 7 he Nature of Linguistic Processing in Reading a Second Language.

Sachs. J . 1967. Recognition memory for syntactic and semantic aspects of connected

Schneider. W.. and R.M. Shiffrin. 1977. Controlled and automatic processing. I . detection,

Seliger. H.W. 1975. Inductive method and deductive method in language teaching: a re-

Shallice. T. 1972. Dual functions of consciousness. Psj~cho/ogicd Review. 79:383-393. Shat i . M. 1977. The relationship between cognitive processes and the development of

communicative skills. In Nebraska Symposium on Morivarion. ed. H.E. Howe and C.B. Keasey. Lincoln. Nebr: University of Nebraska Press.

Shiffrin. R.M.. and W. Schneider. 1977. Controlled and automatic human information processing. I I . perceptual learning, automatic attending. and a general theory. P.yyc.ho/ugica/ Review, 84: 127- 190.

Masters Thesis. Concordia University.

discourse. Perception and Ps.vc.huphy.5ic.s 2:437442.

search. and attention. Psjrhu/ugic.u/ Review 84: 1-66.

examination. I R A L 13: I - 18.

Tarone. E. 1979. Interlanguage as chameleon. Language Lanrning 29:181-191 Tarone. E. 1982. Systematicity and attention in interlanguage. Language Learning 32. Taylor, B.P. 1975. 7he use of overgeneralization and transfer learning strategies by

elementary and intermediate students in ESL. Language Learning 25:73-108. Wode, H. 1978. Developmental principles in naturalistic L2 acquisition. I n Sewnd Longuage

Ac.quisitiun: A Buuk v / Readings. ed. E. Hatch. Rowley. Mass.: Newbury House Press. Wolfe. S. 1981. Bilingualism: One or Two Conceptual Systems. Masters Thesis. San

Francisco State University. Yerkes. R.M..and S.D. Dodson. 1908.Therelationofstrengthofstimulustorapidityofhabit

formation. Journal of Cumpararive Neuro/ug.t, 18:459482.