382 Norman Segalowitz 13 Automaticity and Second Languages NORMAN SEGALOWITZ 1 Introduction There are a number of different ways to understand second language acquisition (SLA), and each has its own strengths and limitations. One currently popular approach to SLA sees it as a special case of complex skill acquisition. From this point of view, one can ask whether SLA shares elements in common with other forms of complex skill acquisition such as learning to play the piano, developing mathematical abilities, or acquiring expertise in making medical diagnosis. In attempting to identify elements that might be common to all forms of complex skill acquisition, cognitive psychologists have focused on a number of issues, including the role of motivation and commitment (Ericsson, Krampe, and Tesch Roemer, 1993; Howe, 1990), the contribution of innate predispositions to mastery in the skill domain (e.g., a talent for language or music; Howe, Davidson, and Sloboda, 1998; Simonton, 1999), the role of practice (Ericsson and Charness, 1994), the operation of memory and attention (Gopher, 1992), and the question of why there exist individual differences in attainment (Ackerman, 1989; Obler, 1989; Obler and Fein, 1988; N. Segalowitz, 1997), among others. One aspect of skill acquisition that has long attracted considerable attention is the development and the role of “automaticity” in performance. This will be the focus of the present chapter. Questions about automaticity are really part of a larger set of questions about the role played by attention and effort in skill acquisition. The inter- connection between automaticity, attention, and skill can be appreciated by considering the following observation, which nearly everyone can attest to. As one’s skill level in a domain increases, the amount of attention and effort required to perform generally appears to decrease. For example, when we begin learning to drive a car, we invest considerable effort in order to per- form well, paying close attention to our every action and decision. We are usually aware that our performance can be easily disrupted by relatively trivial Automaticity 383 distractions, such as someone talking to us. After some amount of practice, however, our skill level improves and, along with this, we no longer experi- ence performing as being as effortful as before. We are now able to pay attention to concurrent events that previously would have disrupted us. Indeed, we often interpret such an escape from the need to concentrate as evidence that skill level has improved. Why, then, does performance become less effortful and more resistant to interference? According to many authors, what has happened is that a number of the underlying components of the performance have become automatic, and it is this change that reduces the need for attention and effort. As will become clear in a moment, the term automatic has a number of different technical meanings. Nevertheless, psychologists generally use the term in a sense similar to what is meant in ordinary language when we say, for example, that 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. Thus, when we perform aspects of a task automatically, we perform them without experiencing the need to invest additional effort and attention (or at least with significantly less effort and attention). When the activity does become automatic in this sense, we often also find that performance has become relatively immune to disruption by potentially interfering events, such as external sights, sounds, concurrently performed tasks, intruding thoughts, or the like. Also, performance appears to be more efficient; it is faster, more accurate, and more stable. Such a transition from non-automatic to automatic performance seems to be a part of nearly all skill acquisition. In language learning, increased performance efficiency can be seen as contributing to fluency, that is, the ability to use language rapidly, smoothly, and accurately. For this reason, understanding what automatic processing is and how it comes about is important for understanding SLA and how to enhance language learning experiences. This chapter contains five further sections. Section 2 considers how auto- maticity has been operationally defined by experimental psychologists. This section deals with what is perhaps the most important issue of all: what automaticity refers to. Section 3 reviews the concept of automaticity as it is found in theories of skill development, including SLA theory. Section 4 discusses some illustrative ways automaticity issues have figured into SLA research. Section 5 discusses the pedagogical implications for SLA that are raised by research on automaticity. Finally, the chapter concludes with a speculative discussion about future directions for research on automaticity in SLA. 2 Operational Definitions of Automaticity To investigate how mechanisms become automatic during the course of skill acquisition, we need precise descriptions and operational definitions of the 384 Norman Segalowitz terms “automatic” and “non-automatic.” Such definitions abound (e.g., Neely, 1977; Newell, 1990; Pashler, 1998; Posner and Snyder, 1975; Schneider and Shiffrin, 1977; Shiffrin and Schneider, 1977). Newell (1990, p. 136), for example, describes automatic processing in the context of searching for a target (say, a particular letter) in a display (of several letters). He characterizes an automatic process as follows: it is fast; it is unstoppable (ballistic); it is independent of the amount of information being processed; it involves exhaustive or complete search of all elements in the display; it involves no awareness of processing; and it involves “pop-out” of the target item from the display. In contrast, non-automatic processing, also called controlled processing, is characterized as follows: it is slow; it is capable of being inhibited; it depends on information load; it involves self-terminating search of the display; it involves awareness; and it does not involve target “pop-out.” Other authors have similarly cited clusters of properties to characterize automaticity. There are two points to be made about such characterizations. One is that they are contrastive. That is, any given characteristic of an automatic process can really only be understood in terms of a corresponding non-automatic, contrasting characteristic. For example, processing can only be considered to be fast in relation to some slower example of processing that serves as a reference point. To demonstrate that some aspect of processing is unstoppable, we need to compare it with a situation in which we observe an ability to interrupt processing. This contrastive aspect of definitions of automaticity is important, as we shall see, because in focusing on the place of automaticity in skill acquisition it is usually necessary to also focus on closely related non-automatic aspects. The second point is that this way of characterizing automaticity gives rise to a set of important questions. For example, should the automatic/non- automatic distinction be viewed as strictly dichotomous (that is, a given process must always be either automatic or not) or as end points of a continuum stretching from very non-automatic to very automatic? Second, should auto- maticity be viewed as a unitary construct? That is, do automatic processes always have the same characteristics (e.g., are always fast, ballistic, immune to interference, etc.)? Or does automaticity refer to a number of possibly related but nevertheless logically independent phenomena? This latter view carries the implication that there exist different types of automaticity. Finally, one can ask whether becoming automatic should be viewed as a central goal of skill attainment or, instead, should be regarded as only one part of the larger picture of what skill acquisition entails. With respect to SLA, interest in automaticity is nearly always connected to concerns about fluency. Is fluency – which we can define here as an ability in the second language to produce or comprehend utterances smoothly, rapidly, and accurately – accompanied by automaticity? Is fluency “merely” highly automatized performance? Do the conditions that promote automaticity necessarily also promote fluency? These and related questions are addressed later in this chapter. Automaticity 385 We turn now to consider some of the different ways automaticity has been discussed and operationalized in the research literature. It is important that we do this for two reasons. One is that, as we shall see, the term “automaticity” has been used to refer to many logically distinct possibilities in the way psychological mechanisms may operate; it is an empirical question whether automaticity in any one of these senses entails automaticity in some or all of the other senses. The second reason is that one often sees reference in the literature to processes becoming or failing to become automatic without further specification of which sense of automaticity is intended. While it may be convenient to use “automaticity” as a shorthand term, the imprecision this entails can potentially create problems for the conduct and interpretation of research on the role of automaticity in skill. 2.1 Fast processing The characteristic most frequently associated with automaticity is speed of processing. It is natural to think that once a mechanism has become automatic it will operate faster than it did earlier.