Chapter 4 Human Learning PDF

82 CHAPTER 4 Human Learning instruction. Skinner was convinced that virtually any subject matter could be taught effectively by a carefully designed program of step-by-step reinforcement. Skinner’s Verbal Behavior (1957) described language as a system of verbal oper- ants,...

82 CHAPTER 4 Human Learning instruction. Skinner was convinced that virtually any subject matter could be taught effectively by a carefully designed program of step-by-step reinforcement. Skinner’s Verbal Behavior (1957) described language as a system of verbal oper- ants, and his understanding of the role of conditioning led to a whole new era in educational practices around the middle of the twentieth century. C LASSROOM C ONNECTIONS One of the hallmarks of Skinnerian psychology was the emphasis on the power of an emitted response—one that comes “willingly” from the learner without an outside stimulus (elicited response) from the teacher. What kinds of emitted responses have you expe- rienced in learning or teaching a language? How would a teacher encourage students to emit if the teacher doesn’t first “tell” the student what to do or say? What kinds of common language class- room activities capitalize on setting the stage for emitted responses by students? A Skinnerian view of both language and language learning strongly influ- enced L2 teaching methodology in middle of the century, leading to a heavy reliance in the classroom on the controlled practice of verbal operants under carefully designed schedules of reinforcement. The popular Audiolingual Method, which will be discussed at the end of this chapter, was a prime example of Skinner’s impact on American language teaching practices in the decades of the 1950s and 1960s. There is much in behavioral theory that is true and valuable, but there is another viewpoint to be considered. We’ve looked at the claim that human behavior can be predicted and controlled and scientifically studied and vali- dated. We have not looked at the notion that human behavior is essentially abstract in nature, composed of such a complex and variable system that most human learning simply cannot be accurately predicted or controlled. We turn next to some paradigms that attempted just such a response to behaviorism. COGNITIVE PERSPECTIVES Cognitive psychology was in many ways a reaction to the inadequacies of behavioral approaches to human learning. Conditioning paradigms were quite sufficient for animal training but mostly failed to account for the network of neurological processes involved in the acquisition of complex skills, the devel- opment of intelligence, the ability of humans to think logically and abstractly, and our enigmatic ability to be creative.  CHAPTER 4 Human Learning 83 Learning as Meaningful Storage and Retrieval David Ausubel (1968) was among the first educational cognitive psychologists to frame a theory of learning that was understandable, practical, and appli- cable to classrooms and teachers. Simply put, he described human learning as a meaningful process of relating (associating) new events or items to already existing cognitive structure (Ausubel, 1965). You might say it’s like hanging new items onto existing cognitive “pegs.” Ausubel’s (1968) perspective accounted for the acquisition of new meanings (knowledge), retention, the organization of knowledge in a hierarchical structure, and the eventual occur- rence of forgetting. Meaningful learning is best understood by contrasting it with rote learning. Ausubel described rote learning as the process of acquiring material as “discrete and relatively isolated entities” (1968, p. 108) that have little or no association with existing cognitive structure. Most of us, for example, can learn a few necessary phone numbers and postal codes by rote without reference to cognitive hierarchical organization. On the other hand, meaningful learning, or subsumption, may be described as a process of relating and anchoring new material to relevant estab- lished entities in cognitive structure. As new material enters our perceptual field, it interacts with, and is appropriately subsumed under, a more inclusive conceptual system. If we think of cognitive structure as a system of building blocks, then rote learning is the process of acquiring isolated blocks with no particular relationship to other blocks. Meaningful learning is the process whereby blocks become an integral part of already established categories or systematic clusters of blocks. For the sake of a visual picture of the distinction, consider the graphic representation in Figures 4.1 and 4.2. Acquisition and Inefficient retention Loss of retention storage of items because of interfering without repeated (triangles) as contiguous items conditioning arbitrary entities Figure 4.1 Schematic representation of rote learning and retention 84 CHAPTER 4 Human Learning Acquisition and Subsumption Systematic “forgetting”; sub- storage of items process sumed items are “pruned” in anchored to an continues favor of a larger, more global established con- in retention conception, which is, in turn, ceptual hierarchy related to other items (ABC) by subsumption in cognitive structure. Figure 4.2 Schematic representation of meaningful learning and retention (subsumption) The significance of the distinction between rote and meaningful learning has tremendous implications for both natural and instructed language acquisi- tion. Recent linguistic research (Ellis & Collins, 2009) has placed emphasis on the role of frequency in language acquisition—a role that fits well with behav- ioral perspectives. But consider the power of meaningfulness (importance, significance, relatability) in the eventual retention of cognitive items. If you carelessly run across a crosswalk and narrowly miss getting hit by a car, you won’t need frequent repetitions of that scare to teach you to be careful. Once is enough! Granted, human beings are capable of learning almost any given item within the so-called “magic seven, plus or minus two” (Miller, 1956) units for perhaps a few seconds. We can remember an unfamiliar phone number, for example, long enough to call the number, after which point the phone number is usually extinguished by interfering factors. Arbitrarily assigned, nonsystem- atically defined numbers are often difficult to retain. To compensate, we can resort to what Smith (1975) called “manufacturing meaningfulness” (p. 162), that is, inventing artificial mnemonic devices to remember a list of items, per- haps for an upcoming examination. Long-term memory is a different matter. A meaningfully learned, sub- sumed item has greater potential for retention. Area codes, postal codes, and street addresses are sometimes efficiently retained since they bear some meaningful relationship to the reality of geographical areas or houses on a street. Names of people are in the same category, but without frequent rein- forcement, could be forgotten. Faces, events, and relationships are clearly anchored in multiple neural circuits, and therefore are good examples of meaningful learning.  CHAPTER 4 Human Learning 85 C LASSROOM C ONNECTIONS Compile a list of a dozen or so different classroom activities or techniques, e.g., pronunciation drill, grammar explanation, free- writing exercise, information-gap group work. Then decide, on a scale of rote to meaningful, from 1 to 10, where the technique falls. Were all your decisions easy to make? Why or why not? Systematic Forgetting and Cognitive “Pruning” Why do we forget things? A behavioral explanation cites infrequency of input, the cessation of practice, and lack of reinforcement. A cognitive perspective takes a much broader view, looking at saliency, relevance, emotion, and the strength of anchoring mental sets that capture a trace of memory. As noted above, an infrequently occurring but very scary (or delightful or romantic) event may be indelibly etched in memory. Once again, Ausubel (1965, 1968) provided a plausible explanation for the universal nature of forgetting. Since rotely learned material is not substantively merged into cognitive structure, its retention is influenced primarily by the inter- fering effects of similar rote material learned immediately before or after the learning task. The consequence of such effects is referred to as proactive and retroactive inhibition. In the case of meaningfully learned material, retention is influenced primarily by the properties of “relevant and cumulatively estab- lished ideational systems in cognitive structure with which the learning task interacts” (Ausubel, 1968, p. 108). Compared to this kind of extended interac- tion, concurrent interfering effects have relatively little influence on meaningful learning, and retention is quite efficient. Hence, in a face-to-face conversation, a person’s physical features are commonly retained as part of a meaningful set, while phone numbers, as isolated unrelatable entities, are easily forgotten. We cannot say, of course, that meaningfully learned material is never for- gotten. But in the case of such learning, forgetting takes place in a much more intentional and systematic manner because it is actually a continuation of the very process of subsumption by which one learns. Forgetting is really a second or “obliterative” stage of subsumption, characterized as “memorial reduction to the least common denominator” (Ausubel, 1963, p. 218). Because it is more economical and less burdensome to retain a single inclusive concept than to remember a large number of more specific items, the importance of a specific item tends to be incorporated, or subsumed, into the generalized meaning of the larger item. In this obliterative stage of subsumption, the specific items become progressively less identifiable as entities in their own right until they are finally no longer available and are said to be forgotten (see Figure 4.2). 86 CHAPTER 4 Human Learning Another way of conceptualizing this second stage of subsumption is in a horticultural metaphor: cognitive pruning (Brown, 1972). When you prune a tree, your aim is to eliminate unnecessary clutter and to clear the way for more growth. Mixing metaphors and switching to the building-block analogy, one might say that at the outset, a structure made of blocks is seen as a few indi- vidual blocks, but as the mind begins to give the structure a perceived shape, some of the single blocks achieve less and less identity in their own right and become subsumed into the larger structure. Finally, the single blocks are lost to perception, or “pruned” out, and the total structure is perceived as a single whole without clearly defined parts. Examples of pruning abound in the development of concepts. Learning that a cup of hot coffee, a pan of boiling water, or an iron, for example, can cause excessive pain is a cognitive process. A small child’s first exposure to such heat may be either direct contact or a verbal “don’t touch!” or “hot!” After a number of exposures to such hot things, the child begins to form a concept of “hotness” by clustering experiences together and forming a gen- eralization. But as time goes on, the bits and pieces of experience that actu- ally built the concept are slowly forgotten—pruned—in favor of the general concept that, in the years that follow, enables the child to avoid burning fingers on hot objects. An important aspect of the pruning stage of learning is that systematic forgetting, or pruning, is not haphazard or chance. Thus by promoting optimal pruning procedures, we have a potential learning situation that will produce retention beyond that normally expected under more traditional theories of forgetting. Interestingly, pruned items may not actually be obliterated. They may be difficult to consciously retrieve, but could still be an integral part of “deep” cognitive structure. The notion of automaticity in SLA may be a case in point. In the early stages of language learning, certain devices (definitions, paradigms, illustrations, or rules) are often used to facilitate subsumption. But in the pro- cess of making language automatic, the devices serve only as “interim” entities, meaningful at a low level of subsumption, and then they are systematically pruned out at later stages of language learning. We might effectively achieve the goal of communicative competence by removing unnecessary barriers to automaticity. A definition, mnemonic device, or a paraphrase might be initially facilitative, but as its need is minimized by larger and more global conceptualizations, it is pruned. For example, a learner in the early stages of acquisition will perhaps overtly learn the rule for when and how to use the present perfect tense. That building block enables the learner to produce past perfect forms correctly and in context, but in later stages the rule ceases to be explicitly retrieved in favor of the automatic pro- duction of the correct verb without any recourse to the rule learned earlier. (More on automaticity in Chapter 9.)  CHAPTER 4 Human Learning 87 C LASSROOM C ONNECTIONS In foreign language classes that you have taken (or taught), what are some specific devices or “tricks” or rules that you used at an early stage, and then no longer needed to “remember” at a later stage? Did you use a mnemonic device, a chart, or an association to recall some aspect of the language? How would your teaching incorporate such pruning as your students move from early to late stages? Research on language attrition has focused on a variety of possible causes for the loss of second language skills (Lambert & Freed, 1982; Weltens, 1987; Weltens & Cohen, 1989; Tomiyama, 2000; Montrul, 2002, 2008, 2011). Some studies have shown that lexical, phonological, or syntactic features may be more vulnerable than idioms, semantic factors, or discourse elements (Andersen, 1982; Nakuma, 1998). Obler (1982) suggested that “neurolinguistic blocking” (left-/right-brain functioning) could contribute to forgetting. Other common rea- sons for language attrition include the following: (1) the strength and conditions of initial learning, (2) the kind of use that a second language has been put to, (3) motivational factors (Gardner, 1982), and (4) cultural identity (Priven, 2002). C LASSROOM C ONNECTIONS Consider the principle of meaningfulness in learning, and the corollary that less relevance or relatability means that forgetting or attrition is likely. What can you do as a learner to help prevent attrition? What kinds of techniques do you think a teacher could use to enhance memory in a language classroom? Attrition is not limited to second language acquisition (Porte, 1999; Isurin, 2000). Native language forgetting can occur in cases of subtractive bilin- gualism (Siegel, 2003; Montrul, 2008, 2011), when learners rely more and more on a second language, which eventually replaces their first language. Often subtractive bilingualism is the result of members of a minority group learning the language of a majority group because the latter denigrates speakers of the minority language. Cognitive psychology provides a strong theoretical basis for the rejection of conditioning models of practice and repetition in language teaching. In a meaningful process like second language learning, mindless repetition, 88 CHAPTER 4 Human Learning imitation, and other rote practices in the language classroom should play only minor short-term roles. Rote learning can be effective on a short-term basis, but for any long-term retention it fails because of a buildup of interference. A case in point was the Audiolingual Method, based almost exclusively on a behavioral theory of conditioning and rote learning. The mechanical “stamping in” of the language through saturation with little reference to meaning was seriously chal- lenged by a more broadly based cognitive view (Ausubel, 1964). Cognitive Linguistics In the 1980s, the place of language in cognition, along with the development of linguistic abilities as an integral component of cognition, became a central focus for linguists and applied linguists. We have already referred to some of the issues surrounding language and thought, the place of language acquisi- tion in intellectual development, and cognitive considerations in examining age and acquisition. Such mergers of psychology and linguistics gave rise not only to psycholinguistics as a field in its own right, but also to what has come to be called cognitive linguistics (Evans & Green, 2006; Verspoor & Tyler, 2009; Holme, 2012), with its standard-bearing journal, Cognitive Linguistics, leading the way in related research. Generative and nativist traditions in the study of L1 acquisition tended to view language as independent of cognitive and social functioning. In a math- ematically based model, the child was thought to possess a deep structure of syntactic and phonological rules that in turn generated an infinite variety of strings of language. In contrast, many of today’s linguistic researchers are highly attuned to the interrelated dynamics of language and cognition. George Lakoff (1987; Lakoff & Johnson, 1980, 2003) was among the vanguard of such inquiry in examining the rich cognitive and social backdrop of metaphor. Soon, inspired by linguists like Deborah Tannen (1990, 1996) and Leonard Talmy (2003), among others, we could no longer look at a child’s or adult’s language acquisition as simply the computational generation of language divorced from cognitive, functional, and pragmatic contexts. C LASSROOM C ONNECTIONS Metaphor is a pervasive and profound characteristic of human language. Examples: journey metaphors (“I’m on the road to suc- cess”); direction metaphors (“Back in 1951...”); war metaphors (“The Yankees battled the Red Sox”). In a language that you have learned, think of a few such metaphors that may have posed some difficulty. What are they? How would you as a teacher help students to conceptualize them?  CHAPTER 4 Human Learning 89 Several themes characterize cognitive linguistic approaches (Croft & Cruse, 2004; Evans & Green, 2006; Robinson & Ellis, 2008): 1. Language is not an autonomous faculty. 2. Syntax is not simply an arbitrary set of rules but rather is interwoven with conceptualization and knowledge. 3. Language ability cannot be examined without concurrent consideration of language use. In the last part of the twentieth century, as studies in L1 and L2 acquisition continued to probe the place of language in human development, it became increasingly obvious that language is interconnected with cognitive concepts such as perception, memory, categorization, meaning, and attention (Robinson & Ellis, 2008). Cognitive linguistics was applied to teaching methodology by Holme (2012), who designed a pedagogical model for the L2 classroom. He incorpo- rated concepts of “embodiment” (metaphor), the reality of lexicon and grammar, concept formation, and usage to form cornerstones for understanding class- room approaches and techniques. It is safe to conclude that cognitive linguis- tics is not so much a radical new field of inquiry as it is the result of a coalescence of research findings and the merging of many strands of research, all of which seek to establish the relationship between language and our com- plex neural networks. SOCIAL-CONSTRUCTIVIST PERSPECTIVES Another manifestation of increasing sophistication in research on language acquisition and human learning was the incorporation of social and affective factors into various theoretical propositions. We have already discussed the importance of the socio-affective domain in previous chapters, and there is more to come in Chapters 6 and 7. For now, a discussion of learning theory would fall short without an examination of what have been called social- constructivist perspectives. We’ll highlight three iconic figures here to charac- terize this side of learning: Carl Rogers, Paolo Freire, and Lev Vygotsky. Carl Rogers Rogers is not traditionally thought of as a “learning” psychologist, yet his work had a significant impact on our present understanding of learning, particularly in educational contexts. His views on humanistic psychology emanated from his classic work Client-Centered Therapy (1951), an analysis of human behavior in terms of a “phenomenological” perspective, a perspective in sharp contrast to his contemporary, Skinner. Rogers saw the “whole person” as a physical and cognitive, but primarily emotional being. “Fully functioning 90 CHAPTER 4 Human Learning persons,” according to Rogers, live at peace with all of their feelings and reac- tions; they are able to reach their full potential (Rogers, 1977). Rogers’s position has important implications for education (Curran, 1972; Rogers, 1983; O’Hara, 2003) by focusing away from “teaching” and toward “learning” or, in O’Hara’s (2003) terms, “transformative pedagogy.” The goal of education is the facilitation of change and learning. Learning how to learn is more important than being taught something from the “superior” vantage point of a teacher who unilaterally decides what shall be taught. Many of our present systems of education, in prescribing curricular goals and dictating objectives, deny persons both freedom and dignity. What is needed, according to Rogers, is for teachers to become facilitators of learning, discarding masks of superiority and omniscience. Teachers also need to have genuine trust and acceptance of the student as a worthy, valuable individual, and to keep open lines of communication between student and teacher. We can see in Rogers’s humanism a radical departure from the scientific analysis of behavioral psychology and even from strictly cognitive theories. Rogers was not as concerned about the actual cognitive process of learning because, he felt, if the context for learning is properly created with due atten- tion to students’ affective states, then they will learn everything they need to. Of course, teachers could take the nondirective approach too far, to the point that valuable time is lost in the process of allowing students to “discover” facts and principles for themselves. Also, a nonthreatening environment might become so “warm and fuzzy” that the facilitative tension needed for learning is absent. There is ample research documenting the positive effects of competi- tiveness in a classroom, as long as that competitiveness does not damage self- esteem and hinder motivation to learn (Bailey, 1983). Paolo Freire Another giant in educational theory is Brazilian educator Paolo Freire (1970). Freire vigorously objected to traditional “banking” concepts of education in which teachers think of their task as one of “filling” students “by making deposits of information which [they] consider to constitute true knowledge— deposits which are detached from reality” (1970, p. 62). Instead, Freire argued, students should be allowed to negotiate learning outcomes, to cooperate with teachers and other learners in a process of discovery, and to relate everything they do in school to their reality outside the classroom. It was the need to help students to engage in this real-world reality that gave Freire the impetus to pen his seminal work, Pedagogy of the Oppressed (1970), which has since inspired millions of teachers worldwide. Education must be focused on helping students to engage in critical thinking: to look beneath various canons of knowledge and to question that which they are simply told to accept unequivocally. Freire wanted all students to become instruments of their own empowerment, “lifting themselves up by their own  CHAPTER 4 Human Learning 91 bootstraps.” While such “liberationist” views of education should be approached with some caution (Clarke, 1990), learners may nevertheless be empowered to achieve solutions to real problems in the real world. C LASSROOM C ONNECTIONS Rogers and Freire stressed the importance of learner-centered classrooms where the teacher and learners negotiate learning out- comes, engage in discovery learning, and relate the course content to students’ reality outside the classroom. How have you observed these ideas in action in your own language learning (or teaching) experience? What kinds of activities emulate such perspectives? Lev Vygotsky Russian-born Lev Vygotsky (1962, 1978), author of the seminal 1934 work, Thought and Language, went almost unnoticed at the time as the limelight shone on his countryman Pavlov and his behaviorist associates. But in the latter part of the twentieth century, as the shifting sands of psychological research paid due attention to sociocultural and affective factors, Vygotsky’s contributions to human learning were lauded for their unique insights. For Vygotsky the key to understanding higher forms (beyond simply phys- ical reflexes) of human mental activity lay in the mediation of symbols, signs, and language. We comprehend the world around us, perceived events, and systems of knowledge through symbolic tools of numbers, music, art, and, of course, language. In Vygotsky’s view, the task for psychology is “to understand how human social and mental activity is organized through culturally con- structed artifacts and social relationships” (Lantolf, 2000, p. 80). Language is not only an instrument for thought, but also, as Vygotsky so ably emphasized, an ability that develops through social interaction. Language is primarily a tool for communication with other human beings, and it is this symbiotic relationship that is a driving force in the development and growth of cognition. From this sociocultural perspective, a child’s early stages of lan- guage acquisition are an outgrowth of the process of “meaning-making in col- laborative activity with other members of a given culture” (Mitchell & Myles, 2004, p. 200). Interesting, isn’t it, how singularly different the two Russian psychologists were—Pavlov and Vygotsky? Of course, the latter cut his scholarly teeth on Pavlov’s behavioral paradigm that dominated early twentieth century thinking, and saw in that behavioristic perspective a major flaw in the study of human learning (Vygotsky, 1987). 92 CHAPTER 4 Human Learning The work of Rogers, Freire, and Vygotsky contributed significantly to a slow but steady redefinition of the educational process in the last twenty years or so. Educators are increasingly striving to enable learners to understand themselves and to create optimal environments for social interaction and nego- tiation of meaning. Teachers as facilitators are providing nurturing contexts for learners to face real-world issues and to believe in themselves. When teachers rather programmatically feed students quantities of knowledge, which they subsequently devour, those teachers foster a climate of “defensive” learning in which learners—in competition with classmates—try to protect themselves from failure, criticism, and possibly from punishment. Ancient Greek philosophers reminded their audiences of the importance of body, mind, and soul in their inquiry. Likewise, the three major perspectives that have been described here—behavioral, cognitive, and social construc- tivist—allow us to put together a comprehensive understanding of human learning and cognition. A behavioral theory helps us to understand some fun- damentals of learning for all organisms. Cognitive viewpoints have multiplied our appreciation of the intricacies of the uniquely human language-thought connection. And without coming full circle (triangle?) to affectively based socio- cultural insights, our understanding would not be balanced. An open-minded twenty-first century view is enriched by considering the benefits and draw- backs of each side of the age-old Greek triangle. C LASSROOM C ONNECTIONS Rogers and Freire stressed the importance of learner-centered classrooms where the teacher and learners negotiate learning outcomes, engage in discovery learning, and relate the course content to students’ reality outside the classroom. How have you observed these ideas in action in your own language learning (or teaching) experience? TABLE 4.1 Perspectives on human learning Behavioral Cognitive Social-Constructivist Conditioning Language-cognition Learner autonomy Rewards connection Whole-person Stimulus-response Meaningful learning Empowerment connections Subsumption Social interaction Reinforcement Systematic forgetting Language as mediation Emphasis: physical Emphasis: mental Emphasis: socioaffective  CHAPTER 4 Human Learning 93 FUNDAMENTAL CONCEPTS IN HUMAN LEARNING Theories of learning do not capture all of the possible general principles of human learning. In addition to the three theoretical perspectives in the first part of the chapter, there are a number of concepts, categories, and types of human learning applicable to SLA. Types of Learning Robert Gagné (1965, pp. 58–59) ably demonstrated the importance of identi- fying a number of universal types of human learning. Let’s take a look at how these concepts apply to language acquisition research. 1. Signal learning. Attending to something in one’s environment (music, animal sounds, human voices, etc.), typical of Pavlovian classical condi- tioning. Linguistic application: human beings notice and attend to human language. 2. Stimulus–response learning. The learner makes a response to a “dis- criminated” stimulus, a specific attendance to a single element in one’s perceptual environment. Linguistic application: Noticing and responding to specific sounds, words, and nonverbal gestures, and receiving a reward for the response. 3. Chaining. Learning a chain of two or more stimulus-response connec- tions. Linguistic application: Stringing several sounds or words together to attempt to communicate meaning. 4. Verbal association. Attaching meaning to verbal/nonverbal chains. Linguistic application: Assigning meaning to various verbal stimuli. “Nonsense” syllables become meaningful for communication. 5. Multiple discrimination. Learning to make different responses to many varying stimuli, which may resemble each other. Linguistic application: Noticing differences between/among sounds, words, or phrases that are similar. For example, minimal pairs (sheep/ship), homonyms (left/left), and synonyms (maybe/perhaps). 6. Concept learning. Learning to make a common response to a class of stimuli even though the individual members of that class may differ widely from each other. Linguistic application: The word “hot” applies to stoves, candles, and irons; young children learn that four-legged farm animals are not all “horsies.” 7. Principle learning. Learning a chain of two or more concepts, a cluster of related concepts. Linguistic application: Verbs in the past tense are classified into regular and irregular forms, yet both forms express the con- cept of tense. 8. Problem solving. Previously acquired concepts and principles are com- bined in a conscious focus on an unresolved or ambiguous set of events. 94 CHAPTER 4 Human Learning Linguistic application: Learning that metaphorical language is not simply idiosyncratic, but connected to cultural world views and ways of thinking, thus explaining why a dead person is “gone.” Also, using language to solve problems, such as information gap exercises in a classroom. You may notice that the first five types fit easily into a behavioral frame- work, while the last three are better explained by cognitive or sociocultural perspectives. Since all eight types of learning are relevant to second language learning, a cautious implication is that certain lower-level aspects of SLA may be more effectively treated by behavioral approaches and methods, while cer- tain higher-order types are more effectively taught by methods derived from cognitive or sociocultural approaches to learning. Methods of teaching, in rec- ognizing different levels of learning, need to be consonant with whichever aspect of language is being taught at a particular time while also recognizing the interrelatedness of all levels of language learning. C LASSROOM C ONNECTIONS Can you add some further SLA examples to each of the eight types of learning above? What kinds of classroom activities would be appropriate for teaching each type? So, in #7, how would you teach regular and irregular verbs? What kinds of learning pro- cesses would the learner be using? Transfer and Interference Human beings approach any new problem by using whatever cognitive struc- tures they possess to attempt a solution, more technically described as the interaction of previously learned material with a present learning event. From the beginning of life, we build a structure of knowledge by the accumulation of experiences and by the storage of aspects of those experiences in memory. Each of those billions of neural bytes become associated with other pieces of our memory, and in the process, some of those connections are bound to facilitate and some are destined to debilitate. Let’s consider this phenomenon in terms of three associated concepts in learning: transfer, interference, and overgeneralization. Transfer usually refers to the carryover of previous performance or knowl- edge to subsequent learning. (It can also apply to the effect of a current act of learning on previously learned material, which is known as retroactive transfer, but we’ll deal with that in a moment.) Positive transfer occurs when  CHAPTER 4 Human Learning 95 the prior knowledge benefits the learning task—that is, when a previous item is correctly applied to present subject matter. Negative transfer occurs when previous performance disrupts or inhibits the performance of a second task. The latter can be referred to as interference, in that previously learned material conflicts with subsequent material—a previous item is incorrectly transferred or incorrectly associated with an item to be learned. A nonlanguage example: Eight-year-old Kaliana has already learned to ride a bicycle, and now attempts to ride her newly acquired skateboard. She posi- tively transfers the psychomotor process of keeping her balance on a moving vehicle. So far, so good. However, she negatively transfers the experience of steering a front wheel for balance to the skateboard, which results in a skinned knee. Eventually she learns that steering on a skateboard is accomplished by a combination of footwork and leaning the body. The most salient example in SLA is the effect of the first-learned native language on the second. Many L2 courses warn teachers and students of the perils of such negative transfer, in fact, the L1 is usually an immediately noticeable source of error among learners. The saliency of L1-L2 interfer- ence has been so strong that it was once fashionable to view second lan- guage learning as exclusively involving overcoming the effects of the native language (Stockwell, Bowen, & Martin, 1965; Wardhaugh, 1970). Is this a fair picture? One’s native language, an obvious set of prior experiences, is frequently negatively transferred. For example, a French native speaker might say in English, “I am in New York since January,” a perfectly logical transfer of the comparable French sentence “Je suis à New York depuis janvier.” Because of the negative transfer of the French verb form to English, the French system interfered with production of the correct English form. However, can we not also claim that the native language of an L2 learner may be positively transferred? In which case, can the learner benefit from the facilitating effects of the first language? Consider the above sentence. The correct one-to-one word order correspondence, personal pronoun, preposi- tion, and cognate “January” have all been positively transferred from French to English! A more detailed discussion of the syndrome is provided in Chapter 8. Equally significant for educators is the positive transfer of previous L2 experience on subsequent L2 experience, both within and across languages (Haskell, 2001; Mestre, 2005). Let’s say you studied French in high school and now you take up Spanish in college. One of the goals of your teacher is to help you and your classmates to positively transfer various strategies, mind- sets, linguistic tricks, and cross-cultural knowledge to this newest language. Even more commonly, suppose you have been learning English as a second language for a few months now. You are most certainly acquiring pieces of the language that have a cumulative effect on your current lessons. You could 96 CHAPTER 4 Human Learning claim that you are not only building lexical, syntactic, discourse, and other abilities, but you are also “getting the hang of it,” as your strategic compe- tence improves. A final aspect of positive transfer within a language pertains to the applica- tion of course content to the “real world” outside of the classroom. English for Academic Purposes (EAP), for example, helps students to learn English skills but also to learn the academic “game,” which might be quite new to students studying English in an English-speaking university and country. Learning con- ventions of writing, extensive reading, note-taking, listening to lectures, giving presentations, and taking examinations are all positive side-effects of learning English ( James, 2006, 2010; DePalma & Ringer, 2011). Of significant interest for some linguists is the retroactive effect of a second language on the first. It is not uncommon for those who take up residence in a foreign country not only to learn the language of their new home, but also for their native language to be “affected.” This phenomenon is found among some bilinguals whose home language is the nondominant lan- guage of their country of residence. Spanish in the United States is an example (Montrul, 2011). Also, American professionals who spend perhaps a decade in Japan or Thailand, as a random example, may come back to the United States with “something funny” about the way they talk, according to friends and family. Overgeneralization In the literature on SLA, interference is almost as frequent a term as overgen- eralization, which is simply a form of negative transfer. Generalization involves inferring or deriving a law, rule, or conclusion from the observation of particular instances. In terms of the previously discussed meaningful learning, items are subsumed (generalized) under higher-order categories for meaningful retention. Concept learning for children is the generalization of a principle from experience with particulars. A child learns that ice cream is delicious from a few encounters with the cold, sweet taste. Usually very few encounters are required! The concept of future time, often mediated by lan- guage, is a generalization from particulars. In SLA it is customary to refer to overgeneralization as a process that occurs as the L2 learner acts within the target language, generalizing a partic- ular rule or item in the L2—irrespective of the L1—beyond legitimate bounds. We have already observed that children acquiring English as a native language overgeneralize regular past tense endings (walked, opened) as applicable to all past tense forms (goed, flied) until they recognize a subset of verbs that belong in an “irregular” category. L2 learners from all native language backgrounds overgeneralize within the target language: In English, “John doesn’t can study” or “He told me when should I get off the train” are common examples. (Again, more on this in Chapter 8.)  CHAPTER 4 Human Learning 97 C LASSROOM C ONNECTIONS In a language that you have learned, think of instances where you encountered interference (from your L1) and overgeneralization (within the L2). Beyond simply informing students of errors and their sources, how would you help students in a classroom to overcome the negative effects of interference and overgeneraliza- tion? What activities or pair work or games could be used? Transfer Positive (+) Negative (–) Overgeneralization Interference (L1 → L1) (L1 → L2) (L2 → L2) (L2 → L1) Figure 4.3 Transfer, overgeneralization, and interference Inductive and Deductive Reasoning Inductive and deductive reasoning are two polar aspects of the generalization process. In the case of inductive reasoning, one stores a number of specific instances and induces a general law or rule or conclusion that governs or sub- sumes the specific instances. Deductive reasoning is a movement from a generalization to specific instances: A general principle allows a person to infer specific facts. L1 learning and natural or untutored SLA involve a largely inductive pro- cess: Learners must infer certain rules and meanings from all the data around them. Most of those rules are learned implicitly, without “conscious,” explicit ability to verbalize them. Classroom language learning tends to rely—more than it should, no doubt—on deductive reasoning. Traditional methods overemphasize the use of deductive reasoning by requiring explicit access to a rule with subsequent attention to its instances. Much of the evidence in communicative L2 learning 98 CHAPTER 4 Human Learning points to the overall superiority of an inductive approach; however, in the case of form-focused instruction (see Chapter 9), learners might reap the benefit of the positive effects of having errors called to their attention. An interesting extension of the inductive/deductive dichotomy was reported in Peters’ (1981) case study of a child learning a first language. Peters found that her subject manifested a number of “Gestalt” characteristics, producing “wholes” in the form of intonation patterns well before speaking the particular words that made up the sentences. Peters cited other evidence of Gestalt learning in chil- dren and concluded that such “sentence learners” (vs. “word learners”) may be more common than researchers had previously assumed. In L2 teaching, Wong (1986) capitalized on just such a concept in a discus- sion of teaching communicative oral production. She advocated explicitly teaching overall intonation patterns for greetings, yes-no questions, and syllable stress before learners had tackled their specific syntactic forms. She was one of the first to advocate the use of kazoos in pronunciation classes so that learners could more easily hear overall sentence stress and intonation. LANGUAGE APTITUDE The discussion so far in this chapter has focused on perception, storage, and recall. Little has been said about a related and somewhat controversial issue in SLA, language aptitude. A number of questions emerge: 1. Is there an ability or “talent” that we can call foreign language aptitude? 2. If so, what is it, and is it innate or environmentally nurtured? 3. Is it a distinct ability or is it an aspect of general cognitive abilities? 4. Does aptitude vary by age and by whether learning is implicit or explicit? 5. Can aptitude be reliably measured? 6. If so, do such assessments predict success in learning an L2? Do certain people have a “knack” for learning foreign languages? Anecdotal evidence would suggest that some people are indeed able to learn languages faster and more efficiently than others. One way of looking at such aptitude is the identification of characteristics of successful language learners. Risk-taking behavior, memory efficiency, intelligent guessing, willingness to communicate, low anxiety, and ambiguity tolerance are but a few of the many variables that have been cited (Rubin & Thompson, 1982; Brown, 1991; Dörnyei & Skehan, 2003; Dörnyei, 2005, 2009; Robinson, 2005). Such factors will be the focus of the next chapter in this book. Historically, research on language aptitude has been a roller-coaster ride. John Carroll’s (Carroll & Sapon, 1959) pioneering work on aptitude, embodied in the Modern Language Aptitude Test (MLAT), began the quest. The MLAT asserted the predictability of number learning, sound discrimination, pattern discernment, and memorization for future success in a foreign language. This test, along with  CHAPTER 4 Human Learning 99 the Pimsleur Language Aptitude Battery (PLAB) (Pimsleur, 1966) and the Defense Language Aptitude Battery (DLAB) (Peterson & Al-Haik, 1976) were used for some time in such contexts as Peace Corps volunteer training programs and military communications courses to help predict successful language learners. The above-mentioned aptitude tests were initially well received by L2 teachers and administrators, especially in view of their reportedly high correla- tions with ultimate success in language classrooms. But slowly their popularity waned, even in the absence of alternative measures of language aptitude (Parry & Child, 1990; Skehan, 1998). Two factors accounted for the decline. First, even though the paper-and-pencil tests claimed to measure language aptitude, it soon became apparent that they more than likely reflected the general intelli- gence or academic ability of a student in any instructional setting (Skehan, 1989; DeKeyser & Koeth, 2011). At best, they appeared to measure ability to perform focused, analytical, context-reduced activities that occupy a student in a traditional language classroom. They hardly even began to tap into the kinds of learning strategies and styles that subsequent research (Ehrman, 1990; Oxford, 1990b, 1996; Reid, 1995; Chamot, 2005; Cohen, 1998) showed to be crucial in the acquisition of communicative competence in context-embedded situations. As we will see in the next chapter, learners can be successful for a multitude of reasons, many of which are much more related to focus and determination than to so-called “native” abilities (Lett & O’Mara, 1990). Second, how is one to interpret a language aptitude test? Rarely does an institution have the luxury or capability to test people before they take a for- eign language in order to counsel certain people out of their decision to do so. And in cases where an aptitude test might be administered, isn’t such a test likely to bias both student and teacher? Both are led to believe that they will be successful or unsuccessful, depending on the aptitude test score, and a self- fulfilling prophecy is likely to occur. Isn’t it wiser for teachers to be optimistic for all their students? By monitoring individual differences and abilities, teachers can steer the student toward strategies that will aid learning and away from those blocking factors that will hinder the process. In the decades that followed the flurry of administrations of standardized aptitude tests, interest declined. But then, in the late 1990s, we saw renewed efforts to address aptitude factors (Sasaki, 1993a, 1993b; Harley & Hart, 1997). A new era of aptitude research was launched with Skehan’s (1998) exposure of the weaknesses of previous aptitude constructs, and his proposal to look at aptitude from a broader view of SLA that incorporates input processing, induc- tive language learning, output strategies, and fluency. The birth of the new millennium witnessed a resurgence of interest language aptitude (Grigorenko, Sternberg, & Ehrman, 2000; Robinson, 2001, 2002, 2005; Skehan, 2002; Dörnyei & Skehan, 2003). Grigorenko, Sternberg, and Ehrman (2000) proposed an aptitude battery based on Sternberg’s theory of intelligence (see the next section in this chapter), the CANAL-F test (Cognitive Ability for 100 CHAPTER 4 Human Learning Novelty in Acquisition of Language—Foreign). This battery differed from previous ones in its involvement of the test taker in a process of learning a simulated lan- guage embedded in a multifaceted language context. Further, it was dynamic rather than static in that it measured the ability to learn at the time of taking the test. Dörnyei and Skehan (2003) followed up on the renewed interest in aptitude with the suggestion that aptitude may be related to varying processes of SLA. So, for example, aptitude constructs such as attention and short-term memory could be relevant for processing input in an L2; phonemic coding ability could contribute to noticing of phonological patterns; and constructs like inductive learning, chunking, and retrieval abilities may allow a learner to identify and integrate gram- matical patterns. Dörnyei and Skehan also cite other research to conclude that “aptitude is relevant not simply for conventional, explicit, rule-focused teaching contexts, but also when the learning is implicit [in natural contexts]” (p. 600). More recently, Robinson (2001, 2002, 2005) and Dörnyei (2005, 2009) sug- gested that aptitude “has been increasingly seen as too broad an umbrella term, one that refers to an unspecified mixture of cognitive variables” (Dörnyei, 2009, pp. 182–183). DeKeyser and Koeth (2011, p. 396) conceded that “there is no unitary construct of aptitude” and that because it is an encompassing term, one should simply refer to “aptitudes, in the plural, for learning a second language.” Robinson (2005) suggested that aptitude is a complex of abilities that include processing speed, short- and long-term memory, rote memory, planning time, pragmatic abilities, interactional intelligence, emotional intelligence, and self- efficacy. Dörnyei (2009) noted that motivation, learning styles, learning strate- gies, anxiety, and other individual differences in language learners may also be related to a learner’s eventual success in learning an L2. Robinson and Dörnyei both appear to agree that none of the above “static or linear presuppositions” ( Jessner, 2008, p. 270) can be sufficiently singled out as a trait or measurable factor in aptitude. Instead, we are better served by viewing the process of SLA as an involvement of dynamic systems theory, “one of com- plexity, with all parts of the system being interconnected, and of ongoing change that results from the multiple interacting influences” (Dörnyei, 2009, pp. 103–104). C LASSROOM C ONNECTIONS The so-called “knack” for learning a language appears to be an elusive factor. But if you were to brainstorm some of what you think are the most important ingredients of language aptitude, what would your “top 5” factors be? Have you invoked any of those abilities within you in your foreign language learning? Using those five factors, how would you, as a teacher, help stu- dents to capitalize on their “gifts” and to compensate for abilities they may not appear to have?  CHAPTER 4 Human Learning 101 INTELLIGENCE AND LANGUAGE LEARNING Intelligence, a construct with multiple definitions and theories, has tradi- tionally been defined and measured in terms of linguistic and logical-math- ematical abilities. The notion of IQ (Intelligence Quotient) is based on several generations of testing of these two domains, stemming from the early twentieth-century research of Alfred Binet, creator of the famous Stanford-Binet Intelligence Scales. Success in educational institutions and in life in general has been shown repeatedly to correlate with high IQ scores (Slavin, 2011). Does IQ correlate equally well with successful SLA? Will a smart person be capable of learning a second language successfully because of high intelli- gence? Not according to a good deal of research and observation over the last few decades. It appears that our “language learning IQs” involve more than simply academic “smarts.” Howard Gardner (1983, 1999, 2006, 2011) was the first psychologist to help us to see why IQ is too simplistic a concept to account for a whole host of skills and abilities. Gardner (1983) initially posited seven different intelli- gences that provided a comprehensive picture of intelligence. He later added one more intelligence, naturalist (Gardner, 1999, 2004), but has rejected adding spiritual or moral intelligence, as they fail, in his view, to meet established cri- teria. Following are Gardner’s eight multiple intelligences: 1. Linguistic 2. Logical-mathematical 3. Musical (the ability to perceive and create pitch and rhythmic patterns) 4. Spatial (the ability to find one’s way around an environment, to form mental images of reality, and to transform them readily) 5. Bodily-kinesthetic (fine motor movement, athletic prowess) 6. Naturalist (sensitivity to natural objects (plants, animals, clouds)) 7. Interpersonal (the ability to understand others, how they feel, what moti- vates them, how they interact with one another) 8. Intrapersonal intelligence (the ability to see oneself, to develop a sense of self-identity) Gardner maintained that by looking only at the first two categories we rule out a great number of the human being’s mental abilities. And he showed that our traditional definitions of intelligence are culture-bound. The “sixth sense” of a hunter in New Guinea or the navigational abilities of a sailor in Micronesia are not accounted for in Westernized definitions of IQ. His more recent work (Gardner, 2004, 2006, 2011) has focused on applications of his multiple intel- ligences theory to daily human interactions as we manipulate our environment in order to accomplish a variety of purposes. 102 CHAPTER 4 Human Learning In a likewise revolutionary style, Robert Sternberg (1985, 1988) also shook up the world of traditional intelligence measurement. In his triarchic view of intelligence, Sternberg proposed three types of “smartness”: 1. Componential ability for analytical thinking 2. Experiential ability to engage in creative thinking, combining disparate experiences in insightful ways 3. Contextual ability or “street smartness” that enables people to “play the game” of manipulating their environment (others, situations, institutions, contexts) C LASSROOM C ONNECTIONS Consider Gardner’s eight intelligences and Sternberg’s three fac- tors. In your experience learning a foreign language, what tech- niques or activities have you experienced that illustrate these different components? If you are teaching a language, to what extent might you help learners to capitalize on strengths and also to compensate for weaknesses? Sternberg contended that too much of psychometric theory is obsessed with mental speed, and therefore dedicated his research to tests that mea- sure insight, real-life problem solving, “common sense,” getting a wider picture of things, and other practical tasks that are closely related to success in the real world. Like Gardner, Sternberg has also recently provided a prac- tical dimension to his research in publications that demonstrate how prac- tical and creative intelligence can determine one’s success in life (Sternberg, 1997, 2003, 2007). Finally, in another effort to remind us of the bias of traditional definitions and tests of intelligence, Daniel Goleman’s work on emotional intelligence (Goleman, 1995, 1998; Merlevede, Bridoux, & Vandamme, 2001) is persuasive in placing emotion, or what might be called EQ (Emotional Quotient), at the seat of intellectual functioning. The management of even a handful of core emotions—anger, fear, enjoyment, love, disgust, shame, and others—drives and controls efficient cognitive processing. Even more to the point, Goleman argued that “the emotional mind is far quicker than the rational mind, springing into action without even pausing to consider what it is doing. Its quickness precludes the deliberate, analytic reflection that is the hallmark of the thinking mind” (1995, p. 291). Goleman has also more recently followed up with work on social as well as ecological intelligence, in an effort to apply emotional management to practical life situations (Goleman, 2006, 2009).  CHAPTER 4 Human Learning 103 By expanding our understanding of intelligence, we can more easily dis- cern a relationship between intelligence and second language learning. Gardner’s musical intelligence could explain the relative ease that some learners have in perceiving and producing the intonation patterns of a language. Music also appears to facilitate learning, as McGinn, Stokes, and Trier (2005) recently demonstrated. Bodily-kinesthetic modes have already been discussed in con- nection with the learning of the phonology of a language. Interpersonal intel- ligence is of obvious importance in the communicative process. (Intrapersonal factors will be discussed in detail in Chapter 6 of this book.) One might even be able to speculate on the extent to which spatial intelligence, especially a “sense of direction,” may assist the second culture learner in growing comfort- able in a new environment. Sternberg’s experiential and contextual abilities cast further light on com- ponents of the “knack” that some people have for quick, efficient, ostensibly “effortless” SLA. After all, successful language learners frequently display their ability to think creatively “outside the box,” and thus grasp some of the dynamic complexity of SLA. Finally, Goleman’s EQ may be far more important than any other factor in accounting for second language success both in classrooms and in untutored contexts. In Chapter 6 we will expand on the central role of the affective domain in SLA. Educational institutions have recently been applying multiple intelligence theory to a variety of school-oriented contexts. Thomas Armstrong (1993, 1994), for example, focused teachers and learners on “seven ways of being smart,” capitalizing on all forms of intelligence. In foreign language education, Christison (1999, 2005) and others have been successfully applying the concept of multiple intelligences to teaching English as a second or foreign language by showing how each intelligence relates to certain demands in the classroom. A Post Script: Some time ago, John Oller suggested, in an eloquent essay, that language is intelligence. “Language may not be merely a vital link in the social side of intellectual development, it may be the very foundation of intel- ligence itself” (1981a, p. 466). According to Oller, arguments from genetics and neurology suggest “a deep relationship, perhaps even an identity, between intelligence and language ability” (p. 487). The implications of Oller’s hypoth- esis for SLA are enticing. Both first and second languages must be closely tied to meaning in its deepest sense. Effective L2 learning thus links surface forms of a language with meaningful experiences, as we have already noted in cogni- tive learning theory. The strength of that link may indeed be a factor in the complex systems that make up what we call intelligence. LEARNING THEORIES IN THE CLASSROOM: ALM & CLL Two language teaching methods emerged in the last century of language teaching that bear a singular relationship to certain perspectives on learning. The Audiolingual method, inspired by behavioristic principles, and Community