Books for language teaching

SLA

Chapter 6 – Cognition and Language Acquisition

Chapter 6 provides an overview of important cognition and information processing concepts in second language acquisition (SLA). The chapter highlights the role of practice in skill acquisition and discusses Skill Acquisition Theory, which explains how learners move from novice to expert levels in a particular domain. The chapter also delves into the different types of memory, including long-term, short-term, and working memory, and how they are involved in SLA. In particular, working memory, which has a limited capacity and is used for temporary activation, has been the focus of much research in SLA, as it is thought to predict learning rate and ultimate levels of attainment in the L2.

Finally, the chapter explores the relationship between attention and L2 learning, discussing how attention can be voluntary and examining the role of intentionality in L2 learning. It also highlights the possibility of learning without awareness, rules, or intention, and provides examples and research evidence supporting these claims. This chapter offers a comprehensive overview of key concepts related to cognition and information processing in SLA, providing insight into how learners acquire new skills and knowledge in the L2.

Case study 6

Case Study: Improving Attention in L2 Learning

Background: You are a language teacher at a university and you have a group of students who have been struggling to pay attention during L2 lessons. Despite your efforts to engage them, they seem disinterested and often do not retain what was taught. You have tried various teaching techniques, but nothing seems to work. You want to find a solution to help them improve their attention and retention during lessons.

Cognition

Cognition refers to the mental processes involved in acquiring, processing, and using knowledge, including perception, attention, memory, language, and problem-solving (Sternberg & Sternberg, 2011; Friedman & Miyake, 2017). Cognition is essential for everyday life and is involved in many activities such as learning, problem-solving, decision-making, and social interactions. It also plays a crucial role in various fields such as education, psychology, neuroscience, and artificial intelligence.

Understanding cognition is important for improving educational practices and interventions and developing new technologies and treatments for cognitive disorders. For example, research on cognitive processes involved in learning can inform instructional practices and interventions aimed at promoting successful learning outcomes (Bransford, Brown, & Cocking, 2000). Moreover, understanding cognitive processes can help develop new technologies and treatments for cognitive disorders such as Alzheimer’s disease and ADHD (Friedman & Miyake, 2017).

Perception is the process of interpreting sensory information from the environment, such as visual, auditory, and tactile stimuli (Goldstein, 2018). Attention is the ability to selectively focus on relevant information and ignore irrelevant information (Posner & Petersen, 1990). Memory is the ability to encode, store, and retrieve information over time, and it is composed of multiple systems such as sensory memory, short-term memory, and long-term memory (Atkinson & Shiffrin, 1968). Language is the complex system of communication that allows us to express and understand meaning through words and grammar (Chomsky, 1965). Problem-solving is the process of identifying and resolving problems involving various cognitive processes such as planning, decision-making, and reasoning (Newell & Simon, 1972).

According to Ortega (2015), cognition refers to how information is processed and learned by the human mind. The term comes from the Latin verb cognoscere, meaning ‘to get to know’. Second language acquisition (SLA) researchers interested in cognition study what it takes to ‘get to know’ an additional language well enough to use it fluently in comprehension and production.

However, our understanding of second language acquisition as a form of cognition is still limited, as our capacity to investigate relevant questions is shaped by the pace at which new theories and methods become available in neighbouring disciplines and the rate at which SLA researchers become conversant in them (Ortega, 2015).

In cognitive research, the relevant behavioural and neurobiological evidence falls within the range of a few hundred milliseconds to a few seconds, or it consists of larger-scope performance that nevertheless lasts a few minutes to a few hours at most. This is in sharp contrast with many of the data on language learning that SLA researchers normally consider. They involve stretches of discourse, multi-turn interactions with human interlocutors, extended texts, referential and social meaning, and even years of studying, using, or living with an L2 (Ortega, 2015). Ortega (2015) suggests that it is crucial to reference relevant first language (L1) research and identify areas where SLA researchers need future attention. Furthermore, the differences in grain size, temporal and ontological, of the various phenomena that are brought together into cognitive explorations of L2 learning are puzzling.

Cognition in second language acquisition (SLA) refers to the processes by which learners acquire, store, retrieve, and use information related to their second language. According to DeKeyser (2007), cognitive processes involved in second language learning can include attention, perception, memory, and problem-solving.

Attention is important for learners to focus on relevant language input and filter out irrelevant information. Perception involves recognizing and categorizing sounds and words in the new language, which can be challenging for learners due to differences in phonology and grammar between their native and target languages (DeKeyser, 2007). Memory is also crucial in SLA, as learners must retain new vocabulary, grammatical structures, and discourse patterns. Working memory, which temporarily holds and manipulates information, plays an important role in language processing and acquisition (Baddeley, 2007).

Problem-solving is also a cognitive process that is involved in SLA. Learners must identify and resolve communication breakdowns, adjust their language production based on feedback, and apply strategies to overcome linguistic barriers (DeKeyser, 2007). Furthermore, cognitive processes are influenced by individual differences, such as age, aptitude, motivation, and learning strategies. For example, older learners may have a more difficult time with perception and memory due to cognitive decline, while highly motivated learners may be more effective in utilizing problem-solving strategies (DeKeyser, 2007).

Cognitive neuroscience has provided insights into the neural mechanisms underlying SLA in recent years. Research has shown that language learning involves the activation of brain regions involved in attention, memory, and language processing, such as the prefrontal cortex, hippocampus, and left inferior frontal gyrus (Abutalebi & Green, 2016).

Information processing

Information processing is a theoretical framework that explains how the human mind processes information. It emerged in psychology in the 1970s as a reaction against behaviourist theories, which were limited in their ability to explain complex cognitive processes. Information processing became the dominant psychological paradigm of the last third of the twentieth century.

At its core, information processing posits that the human mind is a symbolic processor that engages in mental processes, which operate on mental representations. These mental processes intervene between input and output, with performance being a key word in information processing theories. This is because inferences about mental processes can only be made by inspecting observable behavior during processing while performing tasks.

One example of information processing in SLA is the study of working memory capacity and its relationship with L2 processing and production. Working memory is a limited-capacity system responsible for temporarily storing and manipulating information. In a study by Miyake and Friedman (2012), they found that working memory capacity is related to a variety of cognitive tasks, including language learning. Specifically, their study showed that individual differences in working memory capacity predict differences in L2 processing and production abilities.

Another example of information processing in psychology is the study of attention and its role in learning and memory. Attention is the cognitive process of selectively focusing on certain aspects of the environment while ignoring others. It is a fundamental aspect of information processing because it determines what information is selected for further processing. In a study by Robinson and Paccia-Cooper (2015), they found that attentional focus during L2 input processing can lead to better retention of vocabulary and grammar rules.

Information processing refers to the cognitive processes involved in acquiring, storing, and using information. In psychology, information processing is often studied through the use of models, such as the Atkinson-Shiffrin model, which describes the flow of information through sensory memory, short-term memory, and long-term memory (Atkinson & Shiffrin, 1968). Similarly, in second language acquisition (SLA), information processing has been studied as an important aspect of language learning and use (Robinson, 2003).

One area of research in SLA has focused on processing grammatical structures, such as syntax and morphology. For example, studies using event-related potentials (ERPs) have examined the brain’s response to grammatical violations in second language learners (Hahne & Friederici, 1999). These studies have found that second language learners may process grammatical information differently from native speakers, and that this may be related to the amount and quality of their language input.

Another area of SLA research has focused on working memory’s role in language processing and learning (Baddeley, 1992). Working memory is the cognitive system responsible for temporarily storing and manipulating information. Studies have found that working memory capacity strongly predicts language learning success, particularly for complex linguistic structures such as syntax (Daneman & Carpenter, 1980). Furthermore, training programs aimed at improving working memory have shown promise in improving language learning outcomes (Morrison & Cheung, 2011).

Finally, recent research in SLA has begun examining attention’s role in language processing and learning. Attention is the cognitive system responsible for selectively attending to relevant information while ignoring irrelevant information. Studies have found that attention plays an important role in language learning, particularly for identifying and processing salient features of the language input (Gass & Mackey, 2000).

Information processing is a theoretical framework that explains how the human mind processes information, and it has been applied to the field of SLA to better understand cognitive processes involved in language learning. Working memory and attention are two examples of cognitive processes that have been studied in relation to language learning using an information processing perspective.

The power of practice

The power of practice is an essential concept in second language acquisition. It refers to the idea that repeated exposure to and practice with a new language can lead to proceduralization and automaticity, which in turn enhance the efficiency and accuracy of language processing. Proceduralization refers to the process by which cognitive processes become automated through repeated practice, while automaticity refers to the ability to perform tasks without conscious effort or attention.

An example of the power of practice in SLA is the acquisition of grammar rules. Grammar rules may be learned explicitly through instruction and conscious effort when learning a new language. However, with repeated exposure and practice, these rules can become proceduralized and automatic, leading to more efficient and accurate language processing.

Another example of the power of practice in SLA is the acquisition of vocabulary. As learners are exposed to and practice using new vocabulary in context, the activation and retrieval of that vocabulary becomes more automatic and less effortful. This can enhance the fluency and accuracy of language production.

Research has demonstrated the power of practice in SLA. For example, a study by DeKeyser (2007) found that intensive language instruction that includes a significant amount of practice can lead to significant gains in language proficiency, especially in the areas of grammar and vocabulary. Similarly, a study by Ellis and Shintani (2014) found that repeated practice with a specific grammatical structure led to improved accuracy and fluency in its use.

The power of practice is an essential concept in second language acquisition. It refers to the ability of repeated exposure and practice to lead to proceduralization and automaticity, enhancing the efficiency and accuracy of language processing. Examples include the acquisition of grammar rules and vocabulary. Research has demonstrated the effectiveness of practice in SLA, highlighting the importance of incorporating significant amounts of practice in language instruction.

Skill acquisition theory posits that learning involves the gradual transformation of performance from controlled to automatic through relevant practice over many trials, which allows automatic processes to take over the same performance, a process referred to as proceduralization or automatization (DeKeyser, 2007). For instance, when learning to type, a person initially needs to focus on individual keystrokes and the location of each key on the keyboard, which requires controlled processing. However, with continued practice, the person becomes more efficient and can type without consciously thinking about the location of each key. The process of proceduralization or automatization entails the conversion of declarative or explicit knowledge (knowledge that) into procedural or implicit knowledge (knowledge how) (Anderson, 1982).

In second language acquisition (SLA), L2 learners begin with explicit provision of relevant declarative knowledge, typically through explanations explicitly presented by their teachers or in textbooks. Through practice, this knowledge is converted into the ability to use the language fluently, or implicit-procedural knowledge made up of automatic routines (Ellis, 2015). For example, L2 learners may initially learn the rules for forming the past tense in English through explicit instruction, but with practice, this knowledge becomes automatic and they can use the past tense in conversation without thinking about the rule.

Research has shown that the development of automaticity is essential for successful L2 learning (Segalowitz & Segalowitz, 1993; Segalowitz, 2010). Furthermore, the amount and type of practice necessary for proceduralization to occur may depend on the nature of the skill being learned and individual differences in the learner’s cognitive abilities and motivation (DeKeyser, 2007).

The power of practice is crucial in skill acquisition, including second language acquisition (SLA). According to skill acquisition theory, practice enables the gradual transformation of performance from controlled to automatic, leading to proceduralization or automatization (DeKeyser, 2007). This process involves the conversion of declarative knowledge into procedural knowledge and enables learners to perform tasks with little effort and without conscious attention (Anderson, 1982).

The power of practice is not constant over time and follows the power law of learning, which states that the learning rate slows as the mastery level is approached (Ellis and Schmidt, 1998). For example, a learner who has reached a certain proficiency level may find that additional practice does not significantly improve their speaking ability.

Furthermore, proceduralization is skill-specific, meaning that practice aimed at improving L2 production will help automatize production, while practice focused on L2 comprehension will help automatize comprehension (DeKeyser, 1997). For example, a learner who practices listening to and comprehending spoken language will become more automatic in this skill, while a learner who practices speaking will become more automatic in producing the language.

The ultimate goal of practice is to achieve automaticity, which refers to the automatic and effortless use of implicit-procedural knowledge (Segalowitz, 2003). Automaticity is reflected in fluent comprehension and production, and in lower neural activation patterns, indicating that less cognitive effort is required for task performance (Segalowitz, 2003).

Skill acquisition theory

Skill acquisition theory is an approach in second language acquisition (SLA) that focuses on the process of acquiring skills through practice and the development of automaticity. According to this theory, learning a second language involves the gradual transformation of performance from controlled to automatic, which occurs through repeated practice and feedback.

One of the key principles of skill acquisition theory in SLA is the importance of explicit instruction and practice. Declarative knowledge, or knowledge that can be consciously stated, is initially provided to learners through explicit instruction. This knowledge is then gradually transformed into procedural or implicit knowledge, which can be used without conscious effort. As learners gain more practice and experience, they are able to automatize their skills and perform more fluently and accurately.

Another important aspect of skill acquisition theory is the role of feedback. Feedback is essential in skill acquisition, as it allows learners to monitor their progress and make adjustments to their performance. In SLA, feedback can come from a variety of sources, such as teachers, peers, and self-reflection.

Research in SLA has provided support for the principles of skill acquisition theory. For example, studies have shown that explicit instruction and practice can lead to the development of automaticity in second language skills (DeKeyser, 1997). Additionally, feedback has been found to be an important factor in SLA, as learners who receive regular feedback tend to make greater progress in their language learning (Shute & Glaser, 1990).

Skill acquisition theory provides a useful framework for understanding the second language learning process. By emphasizing the importance of practice, feedback, and the development of automaticity, this theory can help guide instructional practices and promote effective language learning.

DeKeyser’s (1997) study is an exemplary study of skill acquisition theory in SLA. The study examined adult English-speaking learners’ acquisition of Spanish direct object pronouns. The learners received training on the use of the pronouns through explicit instruction and practice in production and comprehension tasks. The study found that learners gradually automated their use of direct object pronouns with practice. The learners were able to use the pronouns more accurately and fluently with fewer errors and hesitations, and their reaction times in comprehension tasks became faster. The study also found that learners’ comprehension and production skills developed at different rates, highlighting the skill-specific nature of proceduralization.

DeKeyser’s study provides evidence for the power of practice and the gradual transformation of performance from controlled to automatic. It also demonstrates the role of explicit instruction in providing declarative knowledge that can be converted into implicit-procedural knowledge through practice. The study supports the notion that proceduralization is a gradual process that develops through relevant practice over many trials, as outlined by skill acquisition theory.

Long-term memory

Long-term memory (LTM) is the type of memory that is responsible for storing and retrieving information for long periods of time, from days to years, or even a lifetime. It has a virtually unlimited capacity to store information and is organized in a hierarchical structure, with different levels of abstraction and interconnected networks of associations among different pieces of information.

LTM is typically divided into two main categories: declarative (explicit) and procedural (implicit) memory. Declarative memory is the conscious and intentional recollection of facts and events, and includes semantic memory (general knowledge about the world) and episodic memory (personal experiences). Procedural memory is the non-conscious and automatic memory for skills, habits, and procedures, and includes motor skills, cognitive skills, and emotional responses.

The encoding, storage, and retrieval of information in LTM involve complex cognitive processes and mechanisms, such as elaboration, rehearsal, organization, and retrieval cues. Elaboration refers to the process of linking new information to existing knowledge or creating new connections among pieces of information. Rehearsal refers to the process of repeating or practicing information in order to strengthen its representation in memory. Organization refers to the process of grouping or categorizing information according to meaningful criteria, such as similarity, difference, or hierarchy. Retrieval cues are external or internal cues that help access or activate stored information.

LTM is a critical component of human cognition and plays a fundamental role in learning, problem-solving, decision-making, and social interaction. It is also subject to age-related decline, neurological disorders, and various types of interference and forgetting, which can have significant implications for everyday functioning and well-being.

Long-term-memory and L2 vocabulary knowledge

Long-term memory (LTM) is essential to language learning, particularly in vocabulary acquisition. According to Baddeley’s (1990) working memory model, LTM is the component of memory responsible for storing and retrieving information that has been acquired in the past and that can be retrieved and used in the present. LTM is divided into two categories: declarative memory and procedural memory. Declarative memory is responsible for storing factual information, while procedural memory is responsible for storing knowledge related to motor skills and habits (Baddeley, 1990).

L2 vocabulary knowledge is an essential component of L2 proficiency, and LTM plays a crucial role in vocabulary acquisition. L2 learners must store new vocabulary items in LTM so that they can retrieve them when needed for communication. The process of storing new vocabulary items in LTM involves the consolidation of new information, which refers to the process by which information becomes more stable and resistant to interference (Mackey, 2016).

One approach to vocabulary acquisition is the use of mnemonics, which are memory aids that help learners remember new vocabulary items by linking them to existing knowledge in LTM (Nation, 2001). Another approach is the use of spaced repetition, which involves the systematic review of previously learned vocabulary items at increasing intervals to strengthen their consolidation in LTM (Roediger & Butler, 2011).

Research has shown that the strength and depth of L2 vocabulary knowledge can affect language proficiency (Schmitt, 2010). Additionally, the type of knowledge stored in LTM can impact the way that learners use vocabulary in communication. For example, declarative knowledge may help learners recognize and understand new words, while procedural knowledge may help learners use new words appropriately in speaking and writing (Nation, 2013).

Long-term memory plays a crucial role in L2 vocabulary knowledge. One well-known phenomenon in L2 vocabulary learning is the receptive-productive gap, which refers to the tendency for learners to know more words receptively (i.e., recognize and understand them when encountered in the input) than productively (i.e., produce them in speech or writing) (Webb, 2008). This gap is particularly pronounced for infrequent or difficult words and tends to decrease as proficiency in the L2 develops.

The mental lexicon, which is the total set of words that a learner knows and can retrieve from long-term memory, is another important aspect of L2 vocabulary knowledge that falls within the purview of explicit-declarative memory. The size of the mental lexicon is influenced by factors such as the frequency and type of input that learners are exposed to and their motivation and individual learning styles (Webb, 2008).

Research by Paul Nation and his colleagues in New Zealand has shed light on the typical vocabulary size of L1 and L2 learners. For example, Nation and Waring (1997) found that a typical five-year-old L1 learner has a vocabulary of about 5,000 word families, while a college-educated adult may have a vocabulary of around 20,000 word families. In contrast, L2 learners face a daunting task in acquiring new vocabulary. Nation (2006) estimates that learners need to acquire at least 3,000 new words to minimally follow conversations in the L2 and up to 9,000 new words to be able to read novels or newspapers in the L2.

LTM is an essential component of L2 vocabulary acquisition and plays a crucial role in consolidating and retrieving new vocabulary items. The use of memory aids such as mnemonics and spaced repetition can help learners strengthen their L2 vocabulary knowledge, and the type of knowledge stored in LTM can impact language proficiency and the ability to use vocabulary appropriately in communication.

Short-term memory

Short-term memory is a type of memory that allows us to store and recall a small amount of information for a short period of time, usually up to 30 seconds (Verywell Mind, 2022). Short-term memory is also known as primary or active memory, because it is involved in holding and recalling information for immediate use, such as a phone number or a password (Magnetic Memory Method, 2022). Short-term memory is also part of a larger system called working memory, which involves manipulating and using the information stored in short-term memory for various cognitive tasks, such as solving a math problem, following a recipe, or planning a trip (Magnetic Memory Method, 2022).

Short-term memory has two main characteristics: limited capacity and limited duration. The capacity of short-term memory refers to how much information it can hold at once. According to Miller (1956), short-term memory capacity is about seven items, plus or minus two. This means that we can remember about seven chunks or pieces of information in short-term memory, such as seven digits, seven words, or seven letters. However, more recent research suggests that short-term memory capacity may be even lower, around four chunks or pieces of information (Verywell Mind, 2022). The duration of short-term memory refers to how long it can retain information. Short-term memory lasts only a few seconds to a minute, unless the information is rehearsed or repeated (Verywell Mind, 2022). Rehearsal is a strategy that involves saying or thinking about the information over and over again to keep it in short-term memory. For example, if you need to remember a phone number, you might keep repeating it to yourself until you dial it.

Short-term memory is also susceptible to interference from new or similar information that enters our mind. Interference is anything that disrupts or prevents the storage or retrieval of information in short-term memory. There are two types of interference: proactive and retroactive. Proactive interference occurs when old information interferes with new information. For example, if you learned a list of words yesterday and today you are trying to learn a new list of words, you might have trouble remembering the new one because of the old one. Retroactive interference occurs when new information interferes with old information. For example, if you learned a list of words today and later you are trying to recall a list of words that you learned yesterday, you might have trouble remembering the old list because of the new list.

Short-term memory plays an important role in cognition and daily functioning. It helps us remember things that we just learned or experienced, such as names, faces, directions, instructions, or facts. It also helps us perform various mental operations and tasks that require attention and concentration. However, short-term memory is not enough for long-term learning and retention. To transfer information from short-term memory to long-term memory, we need to use strategies such as elaboration, organization, imagery, association, or mnemonics. Long-term memory is another type of memory that allows us to store and retrieve large amounts of information for longer periods of time, such as days, months, years, or even a lifetime.

The differences between short-term and long-term memory

Short-term memory and long-term memory are two types of memory that differ in several aspects, such as capacity, duration, function, encoding, storage, and retrieval. Short-term memory is the ability to store and recall a small amount of information for a short period of time, usually up to 30 seconds (Verywell Mind, 2022). Long-term memory is the ability to store and retrieve large amounts of information for longer periods of time, such as days, months, years, or even a lifetime (Magnetic Memory Method, 2022).

The capacity of short-term memory refers to how much information it can hold at once. According to Miller (1956), short-term memory capacity is about seven items, plus or minus two. This means that we can remember about seven chunks or pieces of information in short-term memory, such as seven digits, seven words, or seven letters. However, more recent research suggests that short-term memory capacity may be even lower, around four chunks or pieces of information (Verywell Mind, 2022). Long-term memory capacity refers to how much information it can store indefinitely. Unlike short-term memory, long-term memory seems unlimited (Magnetic Memory Method, 2022). This means that we can store and recall large amounts of information in long-term memory, such as hundreds of names, facts, skills, or events.

The duration of short-term memory refers to how long it can retain information. Short-term memory lasts only a few seconds to a minute, unless the information is rehearsed or repeated (Verywell Mind, 2022). Rehearsal is a strategy that involves saying or thinking about the information over and over again to keep it in short-term memory. For example, if you need to remember a phone number, you might keep repeating it to yourself until you dial it. The duration of long-term memory refers to how long it can preserve information. The duration of long-term memory can last from minutes to a lifetime (Magnetic Memory Method, 2022). However, not all long-term memories are equally durable or accessible. Some long-term memories may fade or become distorted over time due to interference or decay. Some long-term memories may also be harder to retrieve than others due to lack of cues or associations.

The function of short-term memory refers to how it processes information for immediate use. Short-term memory is mainly involved in holding and recalling information for tasks that require attention and concentration (Verywell Mind, 2022). For example, we use short-term memory to remember a phone number, a password, or a grocery list. The function of long-term memory refers to how it stores and retrieves information for later use. Long-term memory is mainly involved in storing and recalling information for tasks that require learning and retention (Magnetic Memory Method, 2022). For example, we use long-term memory to remember our names, birthdays, skills, facts, and events.

The encoding of short-term memory refers to how it attaches meaning to information. Short-term memory encoding is usually shallow and based on surface features such as appearance or sound (Verywell Mind, 2022). For example, we might encode a phone number based on how it looks or sounds. The encoding of long-term memory refers to how it organizes and associates information. Long-term memory encoding is usually deep and based on semantic features such as meaning or relevance (Magnetic Memory Method, 2022). For example, we might encode a name based on its significance or relation to us.

The storage of short-term memory refers to how it keeps information in mind. Short-term memory storage is usually fragile and vulnerable to interference from new or similar information that enters our mind (Verywell Mind, 2022). For example, we might forget a phone number if we hear another number or get distracted by something else. Long-term memory storage refers to how it preserves information in brain structures. Long-term memory storage is usually stable and resistant to interference from other sources of information (Magnetic Memory Method, 2022). For example, we might remember a name even if we encounter other names or stimuli.

The retrieval of short-term memory refers to how it recalls information from mind. Short-term memory retrieval is usually fast and accurate if the information is still available and not interfered with (Verywell Mind, 2022). For example, we might recall a phone number quickly and correctly if we just heard it or repeated it. Long-term memory retrieval refers to how it recalls information from brain structures. Long-term memory retrieval is usually slower and less accurate if the information is faded or distorted (Magnetic Memory Method, 2022). For example, we might recall a name slowly and incorrectly if we have not seen or thought about the person for a long time.

Working memory

Working memory has been studied in the context of second language acquisition (SLA) since the mid-1990s, with a particular focus on its role in individual differences in language learning (Skehan, 1998). According to Baddeley and Hitch’s (1974) working memory model, working memory is a system that temporarily holds and manipulates information during cognitive processing. Working memory is limited in capacity, and its ability to process information is affected by various factors, such as the complexity of the information and the individual’s attentional control.

In SLA, researchers have explored the relationship between working memory capacity and language learning, with some suggesting that those with higher working memory capacities may be more efficient learners (Skehan, 1998). For example, a study by Williams (1999) found that learners with higher working memory capacities were able to process complex syntax more quickly and accurately than those with lower working memory capacities.

However, research on the relationship between working memory and language learning has yielded mixed results. Some studies found no significant correlation between working memory capacity and language proficiency (e.g., Miyake & Friedman, 1998). Moreover, it is not yet clear how working memory capacity might interact with other individual differences, such as motivation or language aptitude, in predicting language learning outcomes (Robinson, 2002).

In terms of universal facts about L2 memory capacity, two observations have attracted attention: the fact that L2 learners tend to have lower working memory capacity than native speakers, and the fact that the processing demands of L2 learning may overload working memory capacity (Skehan, 1998). These observations suggest that working memory capacity may be a critical factor in L2 learning, particularly for learners who are processing complex linguistic input in an unfamiliar language.

Working memory is a limited-capacity system that is responsible for temporarily storing and manipulating information needed to complete complex cognitive tasks (Baddeley, 2012). Working memory is crucial for language learning, as learners must hold and manipulate language information in order to comprehend and produce language.

Working memory capacity is limited and varies between individuals, with the average capacity being around seven items or chunks of information (Cowan, 2010). Chunking refers to the process of grouping smaller pieces of information into larger meaningful units that can be more easily stored in working memory (Baddeley, 2012). This is important for language learners, as they must learn to chunk language information such as vocabulary and grammar rules in order to effectively store and retrieve them from working memory.

Research has shown that working memory capacity strongly predicts language learning success (Daneman & Merikle, 1996). For example, learners with larger working memory capacities have been found to be more successful in language learning tasks such as grammar comprehension and vocabulary acquisition (Service, 1992).

However, working memory capacity is not fixed and can be improved through training (Alloway et al., 2009). Language learners can improve their working memory capacity by engaging in working memory training exercises such as memorizing and recalling lists of words or numbers.

Working memory is a cognitive system that temporarily stores and manipulates information during complex cognitive tasks (Baddeley, 2007). The working memory system is characterized by limited capacity and temporary activation. According to Alan Baddeley, a memory expert from the United Kingdom, information can only be held in working memory for a few seconds unless it is subvocally rehearsed, and the phonological loop plays a crucial role in this process (Baddeley, 2007). This loop helps to store verbal information, such as spoken language, and allows for the maintenance and manipulation of that information over short periods of time.

Nelson Cowan, another prominent memory researcher from the United States, has challenged the traditional distinction between long-term and working memory, suggesting instead that working memory is just the part of memory that becomes activated during a processing event (Cowan, 2005). Cowan argues that activation is central to working memory, and that this system allows for the active maintenance of information in a readily accessible state for use in the near future.

In short, working memory has been identified as a key component in language learning and processing, particularly in relation to individual differences in learning and attainment (Gathercole & Baddeley, 1993). Researchers have suggested that individuals with greater working memory capacity may be better able to process and learn new language information, as they are able to hold and manipulate more information in their minds at one time. This has important implications for language pedagogy, as it suggests that training and improving working memory may lead to more efficient language learning (Baddeley, 2012).

Attention and L2 learning

Attention is a crucial cognitive process for second language (L2) learning, as it allows learners to focus their cognitive resources on the relevant information needed for L2 acquisition (Ellis, 2005). Attention can be defined as the cognitive process by which individuals selectively concentrate on specific aspects of their environment while ignoring others (Posner & Petersen, 1990). In L2 learning, attention plays a vital role in language processing, as learners must attend to a variety of linguistic cues such as grammar, vocabulary, pronunciation, and discourse markers (Gass & Selinker, 2008).

Research has shown that attentional processes can affect L2 learning outcomes. One aspect of attention that has been widely studied in the context of L2 learning is attentional control, which refers to the ability to focus attention on relevant information while suppressing irrelevant or distracting information (Bialystok, 2006). Studies have found that individuals with higher attentional control abilities tend to perform better in L2 learning tasks such as vocabulary acquisition (Linck, Osthus, Koeth, & Bunting, 2014) and grammatical processing (Service, Simola, Metsala, & Maury, 2002).

Another aspect of attention that has been examined in L2 learning is attentional capacity, which refers to the amount of cognitive resources available for attentional processing (Robinson, 2003). Studies have shown that attentional capacity can impact L2 learning outcomes, with learners with higher attentional capacity being able to process more complex linguistic information (Robinson, 2002). For example, a study by Miyake and Friedman (2012) found that participants with higher working memory capacity (which is related to attentional capacity) outperformed those with lower working memory capacity on a grammaticality judgment task.

In addition to attentional control and capacity, the attentional allocation has also been studied in L2 learning. Attentional allocation refers to the distribution of cognitive resources among different aspects of L2 processing (Gass & Selinker, 2008). Research has found that attentional allocation can vary based on the type of L2 task, with some tasks requiring more attention to form (e.g., vocabulary acquisition) and others requiring more attention to meaning (e.g., discourse processing) (Gass & Selinker, 2008).

Attention is a critical component of L2 learning, as it allows learners to focus selectively on relevant linguistic information and allocate cognitive resources efficiently. Attentional control, capacity, and allocation are important aspects of attention that have been found to affect L2 learning outcomes.

Learning without attention

Learning without attention is a concept that refers to the possibility of acquiring new information or skills without consciously paying attention to the relevant stimuli. This idea challenges the traditional view that attention is necessary for learning. Different types of learning without attention exist, such as subliminal, implicit, and passive learning.

Subliminal learning is when stimuli are presented below the threshold of conscious perception, but still affect behavior or cognition. For example, a study by Karremans et al. (2006) showed that subliminal exposure to a brand name increased the preference for that brand, especially when participants were thirsty1

Implicit learning is when complex rules or patterns are learned without explicit instruction or awareness. For example, a study by Reber (1967) showed that participants could learn an artificial grammar without being able to verbalize the rules they had learned2

Passive learning is when stimuli are presented in the background while attention is focused on another task. For example, a study by Berry et al. (2001) showed that participants could learn about subtle changes in visual stimuli without paying attention to them

These types of learning without attention have implications for various domains, such as education, advertising, and cognitive neuroscience. They suggest that the human brain is capable of processing and storing information outside of conscious awareness, and that this information can influence behavior and cognition in various ways.

However, learning without attention also has limitations and controversies. Some researchers argue that attention is always involved in some degree or form in any learning, and that nonattentional learning results from residual or divided attention. Others point out that learning without attention is often weaker, slower, or less flexible than learning with attention, and that it depends on factors such as stimulus salience, individual differences, and task demands. Therefore, more research is needed to clarify the mechanisms and boundaries of learning without attention.

Learning without intention

Learning without intention, also known as incidental learning, refers to learning that occurs without a learner’s conscious effort to learn. It is the result of exposure to information in the environment, and the learning is not the primary goal of the learner’s actions. Incidental learning is often contrasted with intentional learning, in which the learner actively seeks to acquire knowledge or skills.

Research has shown that incidental learning can be effective in both L1 and L2 contexts. For example, in a study by Schmidt and Frota (1986), participants listened to Portuguese sentences while their eye movements were monitored. Participants were not told they would be tested on the sentences later, but they were able to recognize them better than novel sentences in a subsequent recognition task. This indicates that the participants had incidentally learned the sentences.

In another study, Horst, Cobb, and Meara (1998) found that L2 vocabulary learning occurred incidentally during reading for pleasure. Participants read an English text while their eye movements were monitored. Later, they were tested on their knowledge of L2 words that appeared in the text. The participants were able to recognize and define the L2 words better than a control group who did not read the text.

Incidental learning can also occur in classroom settings. For example, Ellis and He (1999) found that students learned L2 grammar incidentally while working on a communicative task. The students were not explicitly taught the grammar points, but they were able to use them correctly in subsequent writing tasks.

Research suggests that incidental learning can be a valuable tool for L2 acquisition. Learners can acquire knowledge and skills without conscious effort, simply by being exposed to language in context. However, intentional learning should not be ignored, as learners may still benefit from explicit instruction and focused practice.

Learning without intention is a concept that refers to the possibility of acquiring new information or skills without deliberately trying to learn them. This idea is related to implicit learning, which is defined as learning that occurs without awareness of what has been learned. Learning without intention can happen in various situations, such as when people are exposed to regularities or patterns in the environment, when they perform tasks that involve implicit rules or structures, or when they engage in activities that are enjoyable or meaningful2

Some examples of learning without intention are:

Learning without intention has implications for various domains, such as education, cognitive psychology, and neuroscience. It suggests that learning can be facilitated by making it more natural, engaging, and meaningful for learners, rather than relying on explicit instruction or memorization. It also suggests that learning can occur unconsciously and automatically, and that it can be influenced by factors such as motivation, emotion, attention, and individual differences.

However, learning without intention also has limitations and challenges. Some researchers argue that learning without intention is not possible or desirable, and that learners need to have clear goals and expectations for their learning outcomes. Others point out that learning without intention is often less efficient, accurate, or generalizable than learning with intention, and that it depends on the quality and quantity of the learning materials and opportunities. Therefore, more research is needed to understand the mechanisms and conditions of learning without intention.

Learning without awareness, also known as implicit learning, occurs when knowledge is acquired unconsciously, without the learner’s conscious intention to learn (Reber, 2013). This type of learning is often contrasted with explicit learning, which involves conscious, intentional efforts to learn new information (Reber, 2013).

One example of implicit learning in SLA is the acquisition of grammar rules. It has been suggested that some grammar rules can be acquired implicitly, without the learner’s conscious awareness of the rules (Ellis, 2005). For example, learners may pick up on the use of articles in English through repeated exposure to language use, without being explicitly taught the rules for their usage.

Research on implicit learning in SLA has shown that it can be an effective way to acquire language knowledge, particularly for aspects of language that are not easily learned through explicit instruction (Robinson, 2011). For example, some studies have found that learners can acquire complex syntax and grammar structures implicitly, even when these structures are not made salient through explicit instruction (Tomlin & Villa, 1994).

One popular method for studying implicit learning in SLA is the artificial grammar learning paradigm, in which learners are exposed to structured sequences of sounds or letters and are asked to identify patterns in the sequences without being given explicit instructions (Service, Simola, Metsala, & Maury, 2002). This paradigm has been used to investigate implicit learning of both phonological and morphological structures in L2 learning (Linck, Osthus, Koeth, & Bunting, 2014).

While implicit learning has been shown to be effective for some aspects of L2 learning, it is important to note that not all aspects of language can be learned implicitly (Ellis, 2005). Additionally, some research has suggested that explicit instruction can be more effective for certain types of language learning tasks (Bialystok, 2006). Therefore, a combination of implicit and explicit learning may be the most effective approach for L2 learners (Gass & Selinker, 2008).

Research on implicit learning in SLA suggests that it is a valuable and effective way for learners to acquire language knowledge, particularly for aspects of language that are not easily learned through explicit instruction. However, it is important to consider that not all aspects of language can be learned implicitly, and a combination of implicit and explicit learning may be the most effective approach.

Learning without awareness is a concept that refers to the possibility of acquiring new information or skills without consciously noticing or remembering the relevant stimuli. This idea is related to implicit learning, which is defined as learning that occurs without awareness of what has been learned.1 Learning without awareness can happen in various situations, such as when people are exposed to regularities or patterns in the environment, when they perform tasks that involve implicit rules or structures, or when they engage in activities that are enjoyable or meaningful2

Some examples of learning without awareness are:

  • Learning a foreign language by watching movies or listening to music in that language, without studying grammar or vocabulary3
  • Learning how to play a musical instrument by playing along with songs or improvising, without following formal instructions or notation4
  • Learning how to ride a bike by trial and error, without being taught the principles of balance and coordination5
  • Learning how to solve puzzles or games by exploring different strategies, without being given explicit feedback or hints.
  • Learning about religious beliefs by being exposed to cultural cues and social influences, without consciously reflecting on them.

However, learning without awareness also has limitations and challenges. Some researchers argue that learning without awareness is not possible or desirable, and that learners need to have clear goals and expectations for their learning outcomes. Others point out that learning without awareness is often less efficient, accurate, or generalizable than learning with awareness, and that it depends on the quality and quantity of the learning materials and opportunities. Therefore, more research is needed to understand the mechanisms and conditions of learning without awareness.

Problem-solving 6

You are an ESL teacher, and one of your students, John, has been struggling to retain new vocabulary words. He often forgets them shortly after learning them, which affects his language learning progress.

What steps will you take to help John improve his vocabulary retention and overcome his difficulties?

Chapter Summary

Chapter 6 explores the various cognitive processes that contribute to second language learning. It begins with an overview of the information processing model and how it relates to language learning. The chapter then discusses the importance of practice and repetition in skill acquisition, drawing on the principles of Skill Acquisition Theory. Next, the focus shifts to long-term memory, which is where much of the language knowledge needed for successful communication is stored. The chapter delves into the different types of memory in long-term memory, including declarative and procedural memory, and how they relate to language learning.

The chapter also examines short-term memory and working memory, which are crucial for processing and retaining information in the moment. It explores the limited capacity of working memory and how it affects language learning, particularly with regards to vocabulary acquisition. Finally, the chapter discusses the role of attention in second language learning, emphasizing the importance of intentional and focused attention to the language input. The concept of incidental learning is also explored, along with research on how learners can acquire language knowledge without being aware of doing so. In short, the chapter highlights the complex interplay between different cognitive processes involved in language learning, and the need for learners to develop and refine these processes in order to achieve proficiency in a second language.

Questions to help review the lesson

  1. What is the difference between long-term memory and short-term memory?
  2. What is working memory, and what are its two main characteristics?
  3. How does attention impact L2 learning?
  4. What is Skill Acquisition Theory, and how does it explain L2 learning?
  5. What is the relationship between practice and L2 learning?
  6. Can L2 learning occur incidentally, without intention or awareness? Provide an example.
  7. What are the three stages of information processing, and how do they relate to L2 learning?
  8. What is the importance of chunking in memory?
  9. How does the amount of working memory capacity impact L2 learning?
  10. What are some strategies for improving working memory in L2 learners?
  11. How does the concept of interlanguage relate to the acquisition of an L2?
  12. Can L2 learning occur without the explicit acquisition of rules? Provide an example.

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Chapter 6 provides an overview of important cognition and information processing concepts in second language acquisition (SLA). The chapter highlights the role of practice in skill acquisition and discusses Skill Acquisition Theory, which explains how learners move from novice to expert levels in a particular domain. The chapter also delves into the different types of…