Chapter 6 – Cognition and Language Acquisition

Case study

Mai is a first-year student learning English. She enjoys watching English videos and usually understands the main ideas. However, she often makes grammar mistakes in speaking and writing, such as missing verb endings, articles, and prepositions. Her teacher notices that Mai focuses mostly on meaning, not language form. In one activity, Mai reads for comprehension only. In another, she underlines grammar forms and compares sentence patterns. Later, she uses the target forms more accurately. Mai also learns new words from songs and social media, but she sometimes knows their meanings without being able to use them correctly in speaking or writing.

Discussion

1. What does Mai’s case show about the role of attention in L2 learning?
2. What is the difference between learning for meaning and noticing language form?
3. How can teachers help students pay more attention to useful language features?

Cognition

In second language acquisition (SLA), cognition refers to the mental processes that enable learners to notice, encode, store, retrieve, and use linguistic information. In cognitive approaches to SLA, the central question is how learners come to know an additional language well enough to comprehend and produce it with increasing fluency and accuracy (Ortega, 2009). Ortega emphasizes that cognition-based SLA research draws heavily on neighboring fields such as psycholinguistics, cognitive psychology, and neuroscience, but also notes that L2 learning often unfolds over much longer timescales and in richer social contexts than the millisecond- or second-level processes commonly examined in laboratory cognition research. This mismatch in timescale and unit of analysis remains one of the major challenges in linking cognitive theory to real-world language development (Ortega, 2009).

From an information-processing perspective, cognition in SLA involves at least three closely related components: attention, memory, and control of processing. Attention is necessary because learners cannot process all aspects of the input at once; they must selectively allocate resources to features that are relevant for learning. Memory is essential because new forms and meanings must be retained long enough to be integrated with prior knowledge. Processing control becomes important as learners move from effortful performance to more fluent and efficient language use (Robinson, 2003; Baddeley, 2003).

Memory has been especially important in cognitive accounts of SLA. Atkinson and Shiffrin’s classic model distinguishes sensory, short-term, and long-term memory, providing a foundational framework for understanding how information moves through the cognitive system (Atkinson & Shiffrin, 1968). Later work on working memory refined this view by showing that temporary storage and active manipulation are crucial for complex activities such as comprehension, reasoning, and language learning. Baddeley argues that working memory supports language by coordinating storage, rehearsal, attentional control, and integration of verbal material, making it highly relevant to vocabulary learning, sentence processing, and L2 performance (Atkinson & Shiffrin, 1968; Baddeley, 1992, 2003).

Recent cognitive-neuroscientific work has also shown that bilingual and multilingual language use depends on networks involved in language control, especially when speakers must select the target language and suppress interference from another language. Abutalebi and Green (2016) review evidence that language control recruits a distributed network including frontal, cingulate, parietal, subcortical, and cerebellar regions. Their review is especially relevant to SLA because it connects language use with broader executive-control processes and shows that cognitive demands in bilingual language use are not limited to vocabulary or grammar alone, but also include monitoring, inhibition, switching, and goal maintenance.

Overall, cognition in SLA is best understood not as a single mechanism but as a coordinated system in which attention, memory, and control interact during language learning and use. Cognitive approaches therefore help explain why some aspects of L2 learning are effortful, why practice matters, and why developing fluent performance requires more than explicit knowledge of rules (Ortega, 2009; Baddeley, 2003; Abutalebi & Green, 2016).

Information Processing

Information processing views learning as the transformation of input into increasingly organized and accessible knowledge through a series of mental operations. Applied to SLA, this framework assumes that learners attend to parts of the input, encode them in memory, compare them with existing knowledge, and gradually build more efficient procedures for comprehension and production (Atkinson & Shiffrin, 1968; Robinson, 2003; Ortega, 2009).

Within this framework, attention is not merely a general mental capacity; it is a gatekeeping mechanism that determines which aspects of the linguistic environment are processed deeply enough to support learning. Robinson (2003) argues that attention and memory are tightly linked in SLA because attended input is more likely to be encoded, maintained, and later retrieved. This makes selective attention central to noticing new forms, mapping form to meaning, and retaining linguistic material across tasks.

Working memory is equally central in information-processing accounts. Baddeley (2003) describes working memory as a multicomponent system responsible for temporary storage and manipulation of information during complex cognitive activity. In language learning, this includes holding words or structures in mind while interpreting meaning, planning an utterance, or integrating new linguistic information into existing representations. Because L2 learners often process less automatically than native speakers, working-memory demands can be especially heavy during early and intermediate stages of learning (Baddeley, 1992, 2003).

Information-processing research in SLA also helps explain why learners may know a rule explicitly but still fail to use it smoothly in real time. The issue is not only whether a learner has knowledge, but whether that knowledge can be accessed quickly and reliably under communicative pressure. This distinction between knowledge and online processing is one reason information-processing approaches have remained influential in SLA theory and pedagogy (Ortega, 2009; Robinson, 2003).

In short, the information-processing perspective explains SLA as a gradual reorganization of cognitive resources: learners must attend to input, hold it in working memory, connect it to prior knowledge, and retrieve it efficiently during use. This framework does not reduce language learning to isolated mental events, but it provides a powerful account of how repeated processing of input can lead to more stable and usable L2 knowledge (Atkinson & Shiffrin, 1968; Baddeley, 2003; Ortega, 2009).

The Power of Practice and Skill Acquisition Theory

A central claim in cognitive SLA is that practice changes the quality of performance. What begins as slow, conscious, and effortful use of language can, through repeated and appropriate practice, become faster, more stable, and less attention-demanding. This idea is formalized in skill acquisition theory, which treats L2 learning as a special case of general skill learning (Anderson, 1982; DeKeyser, 2020).

Anderson’s cognitive skill framework distinguishes between an initial declarative stage, in which learners rely on explicit facts or rules, and later stages in which performance becomes increasingly proceduralized. In this view, practice does not simply strengthen memory; it transforms the format of knowledge, allowing learners to move from knowing about the language to using it more efficiently in real time (Anderson, 1982).

DeKeyser’s work applies this logic directly to SLA. In his 1997 study on morphosyntax, learners who received extensive practice showed gradual gains in accuracy and speed, and the results supported the claim that automatization develops slowly and is highly skill-specific. In other words, practice in comprehension does not automatically transfer fully to production, and vice versa. This is an important pedagogical point because it suggests that different language skills require targeted practice rather than a one-size-fits-all treatment (DeKeyser, 1997).

DeKeyser’s later overview of skill acquisition theory maintains the same core claim: language learning progresses through stages from declarative knowledge to procedural control and, eventually, to more automatic performance. Practice is effective when it is meaningful, repeated, and aligned with the specific skill being developed. Feedback is also important because it helps learners adjust performance during this transition from controlled to automatic processing (DeKeyser, 2020).

The endpoint of this process is often described as automaticity. Segalowitz (2003) argues that automaticity is crucial for fluent L2 performance because it reduces the attentional burden associated with routine aspects of language use. When lower-level processes become more automatic, cognitive resources can be redirected to message formulation, interaction, and discourse management. Automaticity therefore helps explain why fluent performance is not simply a matter of grammatical knowledge but of processing efficiency under time pressure (Segalowitz, 2003).

This cognitive view also clarifies why practice effects are often strongest early on and then become more gradual. As learners gain control, additional improvement usually requires more refined, more intensive, or more task-specific practice. Thus, the power of practice in SLA lies not in mechanical repetition alone, but in repeated opportunities to process and use language in ways that gradually reorganize performance. From this perspective, effective instruction should combine explicit explanation where helpful, substantial practice across relevant modalities, and feedback that supports proceduralization and automaticity (Anderson, 1982; DeKeyser, 1997, 2020; Segalowitz, 2003).

Long-term memory

Long-term memory (LTM) refers to relatively durable memory storage that can retain information over extended periods of time. In classic memory theory, LTM is distinguished from short-term storage by its greater capacity and persistence, although later work has emphasized the interaction between temporary processing and stored knowledge rather than a rigid separation of systems (Atkinson & Shiffrin, 1968; Baddeley, 2012).

A common distinction within LTM is between declarative memory and procedural memory. Declarative memory involves consciously accessible knowledge such as facts, meanings, and experiences, whereas procedural memory supports the gradual automatization of skills and routines. In language learning, this distinction is useful because learners may first acquire explicit knowledge about words and rules and then, through use and practice, develop more proceduralized control over them (Anderson, 1982; DeKeyser, 1997).

Information is retained in long-term memory through processes such as encoding, rehearsal, elaboration, and retrieval. Early models highlighted rehearsal as a control process that supports transfer into more stable memory, while later accounts stress that meaningful organization and repeated retrieval are also central to durable learning (Atkinson & Shiffrin, 1968; Baddeley, 2012). Thus, LTM is not simply a passive store but part of an active cognitive system that supports learning, comprehension, and skilled performance.

Long-term memory and L2 vocabulary knowledge

Long-term memory is central to second language vocabulary acquisition because words must be stored in ways that allow later recognition, recall, and use. Vocabulary knowledge is not limited to form–meaning pairing; it also includes knowledge of use, collocation, association, and context, all of which depend on stable memory representations (Nation, 2001; Schmitt, 2010).

Research has shown that learners’ receptive vocabulary is typically larger than their productive vocabulary. In other words, L2 learners often understand more words than they can actively use in speaking or writing. This receptive–productive gap suggests that vocabulary knowledge develops gradually and unevenly in long-term memory, especially for lower-frequency items (Webb, 2008).

Vocabulary size is also strongly related to successful language use. Nation (2006) argues that learners need substantial lexical coverage for effective reading and listening, which highlights the heavy demands that L2 learning places on long-term memory. From a pedagogical perspective, vocabulary learning is strengthened by repeated exposure, meaningful use, and systematic review, all of which help consolidate lexical items and make them more retrievable over time (Nation, 2001, 2006; Schmitt, 2010).

Short-term memory

Short-term memory refers to the temporary retention of a limited amount of information over a brief period. In classic models, it functions as a short-duration store that supports immediate recall and serves as a bridge to more durable memory systems (Atkinson & Shiffrin, 1968).

Short-term memory is limited in both capacity and duration. Earlier accounts often cited a capacity of about seven units, but later research argued that the effective focus of immediate memory is often closer to about four chunks under many conditions (Cowan, 2001). Information that is not rehearsed or refreshed tends to fade quickly or be displaced by new input, which explains why learners may struggle when too much unfamiliar language is presented at once (Atkinson & Shiffrin, 1968; Cowan, 2001).

Short-term memory is also vulnerable to interference. Similar or competing items may disrupt temporary retention before information is consolidated or connected with prior knowledge. In L2 learning, this helps explain difficulties with unfamiliar sound sequences, dense input, or multiple new forms introduced simultaneously (Atkinson & Shiffrin, 1968).

The differences between short-term and long-term memory

Short-term memory and long-term memory differ mainly in duration, capacity, and function. Short-term memory supports the temporary holding of small amounts of information for immediate processing, whereas long-term memory supports the more enduring storage of knowledge and skills (Atkinson & Shiffrin, 1968; Baddeley, 2012).

Their functions also differ. Short-term memory is mainly involved in maintaining information in an accessible state during ongoing cognitive activity, while long-term memory makes accumulated knowledge available for later use in learning, comprehension, and performance. However, the two systems are closely interconnected because what is temporarily active often depends on prior knowledge, and what is processed successfully may become part of long-term memory (Atkinson & Shiffrin, 1968; Cowan, 2001; Baddeley, 2012).

For this reason, it is more accurate to see short-term and long-term memory as distinct but interdependent parts of a larger memory architecture. In SLA, both are essential: learners must temporarily maintain novel linguistic material while also consolidating vocabulary, structures, and patterns for later retrieval and fluent use (Baddeley, 2012).

Working memory

Working memory is the limited-capacity system responsible for temporarily maintaining and manipulating information during complex cognitive activities such as comprehension, reasoning, and learning (Baddeley & Hitch, 1974; Baddeley, 2012). Unlike a purely passive short-term store, working memory is an active system that supports ongoing mental processing.

Baddeley and Hitch (1974) proposed a multicomponent model of working memory, and Baddeley (2000) later added the episodic buffer to explain how information from different sources can be integrated. This framework has been especially influential in language research because it explains how learners hold words, sounds, meanings, and syntactic information in mind while processing or producing language (Baddeley & Hitch, 1974; Baddeley, 2000, 2012).

An alternative perspective is Cowan’s view that working memory consists of the currently activated portion of long-term memory, with a smaller subset in the focus of attention (Cowan, 2001). This view is important because it highlights the close relationship between temporary processing and stored knowledge rather than treating them as wholly separate systems.

In SLA, working memory has been linked to individual differences in language learning and performance. Learners with stronger working-memory resources may be better able to hold unfamiliar phonological sequences, process complex input, and manage competing linguistic information during comprehension and production (Gathercole & Baddeley, 1993; Service, 1992). However, working memory is best viewed as one important factor among several, rather than as a single predictor of L2 success (Baddeley, 2012).

Attention and L2 learning

Attention is central to second language learning because learners cannot process all aspects of linguistic input at the same time. They must selectively attend to features of the input if those features are to become intake for learning. In SLA, attention has therefore been treated not as a peripheral factor but as a core mechanism linking exposure to acquisition. Tomlin and Villa (1994) argued that attention is not a single undifferentiated process but a system with multiple components, and they proposed that finer distinctions in attentional processing can help explain why some aspects of input are learned while others are not. Robinson (2003) likewise emphasized that attention and memory are closely connected in SLA, since attended input is more likely to be encoded, maintained, and later retrieved.

Schmidt’s work is especially influential here. In his discussion of consciousness and L2 learning, he argued that noticing is necessary for converting input into intake. In this view, learners do not acquire features simply because those features are present in the environment; they must at least notice them at some level. This claim does not mean that all learning must be fully explicit or verbally articulated, but it does mean that completely unattended language input is unlikely to become part of developing L2 knowledge.

For this reason, attention in L2 learning is best understood as selective and limited. Learners distribute their attention differently depending on task demands, proficiency, salience of input, and processing load. Some tasks draw attention more strongly to meaning, while others encourage greater attention to form. This variability helps explain why learners may understand a message without learning a targeted grammatical feature, or may notice a form in one context but ignore it in another.

Learning without attention

The idea of learning without attention has often been discussed in relation to subliminal or highly implicit learning, but the evidence in SLA does not support strong claims that language can be acquired in the complete absence of attention. Schmidt (1990) directly addressed this issue and concluded that subliminal language learning is impossible, while also arguing that noticing is the necessary condition for intake. This position remains one of the clearest rejections of the claim that L2 development can proceed from entirely unattended input.

At the same time, rejecting learning without attention does not mean that all learning must be deliberate or analytically explicit. What the literature suggests is that some level of attention is still involved, even when learners are not intentionally studying language. In other words, learners may acquire language incidentally, but not in the total absence of attentional engagement. Robinson’s account similarly treats attention as essential because it supports encoding and subsequent memory for language input.

Research on implicit learning outside SLA, particularly Reber’s (1967) artificial-grammar experiments, shows that people can become sensitive to patterned regularities without being able to verbalize the rules they have learned. However, these findings should be interpreted cautiously in relation to SLA. They provide evidence that learning can occur with limited conscious rule awareness, but they do not demonstrate that learning occurs with no attention at all.

Learning without intention

Learning without intention is more accurately described in SLA as incidental learning. Here, the learner’s primary goal is not to study language itself, yet language learning still occurs as a by-product of meaning-focused activity. Schmidt (1990) explicitly distinguished this issue from subliminal learning: incidental learning can occur, but it does so when task demands lead learners to pay attention to aspects of the language they encounter. Thus, the absence of intention to learn does not imply the absence of attention.

Incidental vocabulary learning through reading is one of the clearest examples. Horst, Cobb, and Meara (1998) showed that learners can acquire vocabulary while reading for comprehension, even when vocabulary study is not the primary task. Their study is often cited because it demonstrates that lexical growth can emerge from meaning-focused exposure, although the gains are typically partial and gradual rather than complete or immediate.

Task-based vocabulary research also supports this point. Hulstijn and Laufer (2001) found that vocabulary retention depends on the degree of task-induced involvement, particularly the extent to which a task requires need, search, and evaluation. Their findings suggest that incidental learning is not merely a passive result of exposure; it is strengthened when learners are cognitively engaged with lexical items during task performance.

Taken together, these studies show that learning without intention is possible, but it is not effortless or automatic in a simple sense. Incidental learning depends on the nature of the task, the amount of exposure, and the degree to which learners allocate attention to relevant linguistic material while pursuing another goal.

Learning without awareness

Learning without awareness is usually discussed under the label implicit learning. In broad terms, it refers to learning that results in knowledge learners may not be able to explain explicitly. Reber’s (1967) classic artificial-grammar work is foundational here because participants showed sensitivity to grammatical regularities without being able to state the rules that governed them. This work has been highly influential in later discussions of implicit learning in language-related domains.

In SLA, however, the issue is more controversial. Schmidt (1990) argued that complete absence of awareness is difficult to reconcile with evidence from language learning, especially if one distinguishes carefully between awareness of form, awareness of learning, and ability to verbalize rules. His position was not that all L2 learning must be metalinguistically explicit, but that some degree of conscious noticing is required for learning to occur.

Tomlin and Villa (1994) also helped clarify the debate by separating attention from awareness conceptually. Their account leaves room for the possibility that certain component processes of attention may operate without full conscious awareness, but it does not support the stronger claim that language learning proceeds independently of the attentional system. This distinction is useful because it prevents the common error of treating attention, intention, and awareness as interchangeable terms.

A balanced conclusion, therefore, is that SLA research supports limited forms of implicit learning, but not the view that learners acquire language entirely without noticing anything relevant in the input. Learning may occur without an explicit intention to learn and without conscious rule formulation, yet still require attentional engagement with the linguistic material.

Problem-Solving Task: Helping Nam Learn Better

Nam is learning English through videos, songs, and class activities. He understands the main ideas quite well, but he keeps making the same mistakes with grammar and vocabulary in speaking and writing. For example, he often forgets -s in the present simple, uses the wrong prepositions, and cannot use new words correctly in sentences. Nam says, “I understand the lesson, but I don’t notice the small language details.”

Your group is asked to help Nam.

Your task

Discuss the problem and suggest 3 practical solutions to help Nam:

1. pay more attention to important language forms,
2. remember new vocabulary better, and
3. use grammar and vocabulary more accurately in speaking and writing.

Guiding questions

1. What is Nam’s main learning problem?
2. Why is understanding meaning alone not enough?
3. What classroom activities or strategies can help him improve?

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Case study Mai is a first-year student learning English. She enjoys watching English videos and usually understands the main ideas. However, she often makes grammar mistakes in speaking and writing, such as missing verb endings, articles, and prepositions. Her teacher notices that Mai focuses mostly on meaning, not language form. In one activity, Mai reads…