Chapter 7 – Foreign language aptitudes

Posted On April 21, 2023

This chapter explores the concept of language aptitude, which refers to the cognitive and perceptual abilities that facilitate second language (L2) learning and processing. The chapter covers the following topics. First, it introduces the three main dimensions of human psychology that are relevant for L2 learning: cognition (how information is processed and learned by the mind), conation (how will and freedom are used to make choices and actions), and affect (how emotions and feelings influence learning and behavior). The section also discusses how these dimensions are related to each other and to L2 aptitude. Second, this chapter reviews the development and use of aptitude tests, such as the Modern Language Aptitude Test (MLAT), that aim to measure and predict the rate of L2 learning in formal instruction settings. The section also examines the validity and reliability of these tests and their limitations and criticisms.

Third, it explores the possibility that some learners may have difficulties in L2 learning not because of a lack of aptitude, but because of general language-related problems, such as dyslexia or specific language impairment. The section also discusses how to identify and help these learners. Next, this chapter focuses on one of the most important components of L2 aptitude: memory capacity. The section explains how memory capacity affects different aspects of L2 learning and processing, such as phonological awareness, phonetic coding, grammatical sensitivity, vocabulary acquisition, and reading comprehension. The section also suggests some strategies to enhance memory capacity for L2 learning. Also, it examines how memory interacts with other components of L2 aptitude, such as working memory, attentional control, declarative memory, procedural memory, analogical reasoning, pattern recognition, and statistical learning. The section also reviews recent research on these abilities’ cognitive mechanisms and neural correlates.

Fourth, This chapter addresses the question of whether L2 aptitude changes with age. The section reviews some evidence that suggests that aptitude may decline with age, but also some evidence that suggests that aptitude may remain stable or even improve with age. The section also discusses some factors that may influence the relationship between aptitude and age, such as motivation, experience, and training. Fifth, it proposes a new framework for conceptualizing L2 aptitude as a multidimensional construct that is sensitive to the type and stage of L2 learning and processing. The section argues that different aptitude components may be more or less relevant for different types of L2 learning (implicit vs. explicit, incidental vs. intentional) and different types of L2 tasks (input-based vs. output-based, simple vs. complex). The section also suggests some implications for L2 instruction based on this framework.

Finally, it concludes the chapter by highlighting some directions for future research on L2 aptitude. The section suggests that more research is needed on how to define and measure aptitude components and functions more clearly and consistently, how to generalize and apply aptitude findings to naturalistic and diverse settings and populations of learners and languages, and how to use aptitude tests and measures for diagnostic, placement, and instructional purposes.

Case study 7

John is a high school student who has recently decided to learn French. He’s taking French classes as part of his school curriculum, and he’s finding it difficult to keep up with the class. Despite putting in a lot of effort, he’s struggling to remember vocabulary, understand grammar concepts, and speak in French fluently.

John’s teacher suggests that he may have a lack of L2 aptitude, which is making it difficult for him to learn French. However, John is determined to improve his French skills and is willing to try different approaches to make progress.

Work in a group of three or four students, and discuss the ways or steps to help John improve his French language.

Introduction

Foreign language aptitude is a concept that refers to the specific talent or potential that a person has for learning a foreign or second language (L2) (Carroll, 1981). It is influenced by various factors, such as cognitive abilities, learning styles, motivation, and personality traits (Wen, Biedroń & Skehan, 2017). Foreign language aptitude can be measured by formal tests that assess different aspects of language learning, such as phonetic coding ability, grammatical sensitivity, inductive language learning ability, and rote memory (Carroll & Sapon, 1959). These tests are designed to predict a learner’s success with a new language, especially in formal and intensive settings.

Foreign language aptitude theory has evolved over time, from the early conceptions of Carroll and his colleagues in the 1950s and 1960s, to the more recent perspectives and models that incorporate insights from cognitive psychology, second language acquisition (SLA), and cognitive neuroscience. Some of the current theoretical issues and debates include:

The nature and structure of foreign language aptitude: Is it a unitary or a multidimensional construct? How many components does it have and how are they related? How does it interact with other individual differences and contextual factors?
The domain-specificity or domain-generality of foreign language aptitude: Is it a unique ability that is specific to language learning, or is it a manifestation of more general cognitive abilities that can be applied to other domains as well?
The stability or malleability of foreign language aptitude: Is it a fixed trait that is determined by genetic factors and early experiences, or is it a dynamic state that environmental factors and learning strategies can influence?
The role and relevance of foreign language aptitude in different learning contexts and stages: How does it affect the process and outcome of language learning in various settings (e.g., naturalistic vs. instructed; intensive vs. extensive; individual vs. collaborative)? How does it relate to different aspects of language proficiency (e.g., accuracy vs. fluency; explicit vs. implicit knowledge; receptive vs. productive skills)?

Foreign language aptitude refers to an individual’s natural ability to learn a foreign language, and it is often seen as a key factor in predicting language learning success. According to John B. Carroll, who is one of the leading figures in the study of language aptitude, “aptitude refers to an individual’s initial readiness or talent for acquiring proficiency in a particular skill or set of skills” (Carroll, 1981, p. 6). Carroll and other researchers have identified a number of different components that contribute to foreign language aptitude, including phonetic coding ability, grammatical sensitivity, inductive language learning ability, and rote memory ability.

Phonetic coding ability refers to an individual’s ability to hear and produce the sounds of a foreign language accurately. This is important because many languages have sounds that do not exist in the individual’s native language, and it can be difficult to learn to produce these sounds accurately without a strong phonetic coding ability. Grammatical sensitivity refers to an individual’s ability to recognize and understand the rules that govern the structure of a language, including the rules for word order, tense, and agreement. This is important because a good understanding of grammar is essential for communicating effectively in a foreign language.

Inductive language learning ability refers to an individual’s ability to infer patterns and rules from exposure to a foreign language. This is important because language learning often involves a great deal of exposure to the language, and being able to infer patterns and rules from this exposure can help individuals learn the language more quickly and effectively. Rote memory ability refers to an individual’s ability to memorize vocabulary and grammar rules. This is important because learning a foreign language often requires memorizing a large amount of vocabulary and grammar rules, and individuals with strong rote memory ability are likely to find this easier.

There is some debate among researchers about the relative importance of these different components of language aptitude. Some researchers, such as Michael Canale and Merrill Swain, argue that the ability to use language in a communicative context is the most important component of language aptitude (Canale & Swain, 1980). Other researchers, such as Robert Sternberg, argue that cognitive factors such as working memory and executive control are also important for language learning success (Sternberg, 1985).

Research has shown that foreign language aptitude is a strong predictor of language learning success, particularly in the early stages of language learning. For example, a study by Ellen Bialystok and colleagues found that foreign language aptitude better predictor language learning success than cognitive factors such as IQ (Bialystok et al., 2005). Another study by David Birdsong found that individuals with higher levels of foreign language aptitude were able to achieve higher levels of proficiency in a foreign language more quickly than individuals with lower levels of aptitude (Birdsong, 2004).

Foreign language aptitude is a complex construct that involves a number of different components, including phonetic coding ability, grammatical sensitivity, inductive language learning ability, and rote memory ability. Although there is some debate among researchers about the relative importance of these different components, there is general agreement that foreign language aptitude is a strong predictor of language learning success, particularly in the early stages of language learning.

Abrahamsson and Hyltenstam (2008) conducted a study to investigate the role of foreign language aptitude in ultimate attainment of second language (L2) proficiency by adult learners. They compared two groups of L2 speakers of Swedish who had started learning the language after puberty: one group consisted of 39 native-like speakers who had been judged as indistinguishable from native speakers by expert raters, and the other group consisted of 39 non-native-like speakers who had been identified as having a foreign accent by the same raters. The authors hypothesized that the native-like group would have higher levels of language aptitude than the non-native-like group, and that aptitude would be a stronger predictor of L2 proficiency than other factors, such as age of onset, length of exposure, motivation, and cross-linguistic influence.

The study used a battery of tests to measure the participants’ aptitude, L2 proficiency, and first language (L1) background. The aptitude tests included the Modern Language Aptitude Test (MLAT), the LLAMA Language Aptitude Test, and a test of phonetic coding ability. The L2 proficiency tests assessed the participants’ oral production, grammar, vocabulary, and pronunciation. The L1 background questionnaire collected information about the participants’ native languages, education, and language use.

The results showed that the native-like group had significantly higher scores on all aptitude tests than the non-native-like group, and that aptitude accounted for 49% of the variance in L2 proficiency scores. The other factors, such as age of onset, length of exposure, motivation, and cross-linguistic influence, did not have significant effects on L2 proficiency. The authors concluded that a high degree of language aptitude is required for adult learners to reach a native-like level of L2 proficiency, and that aptitude effects are robust and stable across different learning contexts and stages.

The correlational approach to cognition, conation and affect

The correlational approach is a method of research that examines the relationship between two or more variables without manipulating them. It aims to identify patterns of association, direction, and strength of the relationship, and possible causal factors. The correlational approach can be used to explore various aspects of human psychology and behavior, such as cognition, conation, and affect.

Cognition refers to the mental processes involved in acquiring, storing, manipulating, and using information. It includes perception, attention, memory, reasoning, problem-solving, language, and decision-making. Factors such as motivation, emotion, personality, culture, and context influence cognition. Cognition also plays a crucial role in second language acquisition (SLA), as learners need to process linguistic input, produce linguistic output, and develop linguistic knowledge and skills.

Conation refers to the volitional or intentional behavior aspect involving goal-setting, planning, self-regulation, and action. It includes motivation, willpower, persistence, and self-efficacy. Factors such as cognition, emotion, personality, values, and beliefs influence conation. Conation also plays a crucial role in SLA, as learners need to set goals for their language learning, monitor their progress and performance, and adjust their strategies and efforts accordingly.

Affect refers to the emotional or feeling aspect of behavior that involves experiencing and expressing emotions. It includes mood, attitude, emotion regulation, and emotional intelligence. Affect is influenced by various factors, such as cognition, conation, personality, culture, and context. Affect also plays a crucial role in SLA, as learners experience various emotions during their language learning process, such as anxiety, enjoyment, frustration, and satisfaction.

The correlational approach can be used to investigate how cognition, conation, and affect are related to each other and to SLA outcomes. For example,

Ellis (1999) used a correlational approach to examine the relationship between cognitive aptitude and L2 proficiency in a large sample of learners of different languages. He found that aptitude was positively correlated with L2 proficiency across different contexts and stages of learning (more details will be presented the subsequent section).
Bown and White (2011) used a correlational approach to examine the relationship between conation (self-regulation) and affect (emotion regulation) in a small sample of independent learners of Russian. They found that self-regulation and emotion regulation were interrelated and influenced by the learning environment and the quality of relationships within that environment. (more details will be presented the subsequent section).
Dewaele (2018) used a correlational approach to examine the relationship between affect (anxiety) and cognition (self-perceived proficiency) in a large sample of multilinguals. He found that anxiety was negatively correlated with self-perceived proficiency across different languages and contexts. (more details will be presented the subsequent section).

Ellis (1999) conducted a study to explore the relationship between cognitive aptitude and L2 proficiency in a large sample of learners of different languages. He used a correlational approach to examine how aptitude components, such as phonetic coding ability, grammatical sensitivity, inductive learning ability, and rote memory, were associated with L2 proficiency measures, such as vocabulary, grammar, listening, and speaking. He also investigated how aptitude effects varied across different contexts and stages of learning.

The study involved 1,200 participants who were learning one of six languages (English, French, German, Italian, Spanish, or Welsh) in various settings (naturalistic, instructed, or mixed). The participants completed a battery of tests that measured their aptitude and L2 proficiency. The tests included the Modern Language Aptitude Test (MLAT), the LLAMA Language Aptitude Test, and various L2 knowledge and skills tests.

The results showed that aptitude was positively correlated with L2 proficiency across all languages and contexts. The strongest correlations were found between phonetic coding ability and L2 listening and speaking skills, and between grammatical sensitivity and L2 grammar knowledge. The weakest correlations were found between rote memory and L2 vocabulary knowledge. The results also showed that aptitude effects were stronger in naturalistic and mixed settings than in instructed settings, and stronger in early and intermediate stages of learning than in advanced stages.

The study by Ellis (1999) provided empirical evidence for the validity and utility of cognitive aptitude as a predictor of L2 learning success. It also demonstrated the complexity and variability of aptitude effects depending on the language, context, and stage of learning. The author suggested some implications for L2 teaching and testing, such as adapting instruction to learners’ aptitude profiles, designing aptitude tests sensitive to different languages and contexts, and considering learners’ aptitude levels when assessing their L2 proficiency.

Another research by Bown and White (2011) conducted a study to investigate the relationship between conation (self-regulation) and affect (emotion regulation) in a small sample of independent learners of Russian. They used a correlational approach to examine how the learners’ self-regulatory and emotion-regulatory strategies were related to each other and to the learning environment and the quality of relationships within that environment. They also explored how the learners’ cognitive appraisals mediated their emotional experiences and their regulation of emotions.

The study involved 19 participants who were enrolled in an online course of Russian as a foreign language. The participants completed a questionnaire that measured their self-regulation and emotion regulation strategies, as well as their perceptions of the learning environment and the quality of relationships with their instructors and peers. The participants also kept weekly journals that recorded their emotional experiences and their regulation of emotions during their language learning process. The data were analyzed using descriptive statistics, correlation analysis, and qualitative content analysis.

The results showed that self-regulation and emotion regulation were interrelated and influenced by the learning environment and the quality of relationships within that environment. The learners who reported higher levels of self-regulation also reported higher levels of emotion regulation, and vice versa. The learners who perceived the learning environment as more supportive, challenging, and engaging also reported higher self-regulation, emotion regulation, and positive emotions. The learners who had more positive relationships with their instructors and peers also reported higher levels of self-regulation, emotion regulation, and more positive emotions. The results also showed that the learners’ cognitive appraisals mediated their emotional experiences and their regulation of emotions. The learners who appraised the learning tasks as more relevant, meaningful, and achievable experienced more positive emotions and regulated their emotions more effectively than those who appraised the tasks as less relevant, meaningful, or achievable.

The study by Bown and White (2011) provided empirical evidence for the interplay between conation, affect, cognition, and context in language learning. It also demonstrated the importance of considering both self-regulatory and emotion-regulatory strategies as part of language learning processes and outcomes. The authors suggested some implications for language teaching and research, such as fostering a supportive and challenging learning environment, enhancing the quality of relationships among language learners and instructors, and promoting cognitive appraisals that facilitate positive emotions and effective regulation of emotions.

Futher more, Dewaele (2018) conducted a study to investigate the relationship between affect (anxiety) and cognition (self-perceived proficiency) in a large sample of multilinguals. He used a correlational approach to examine how the learners’ levels of foreign language anxiety (FLA) and self-perceived proficiency (SPP) varied across different languages and contexts. He also explored how the learners’ biographical background and personality traits influenced their FLA and SPP.

The study involved 1,746 participants who spoke two or more languages and who completed an online questionnaire. The questionnaire measured their FLA and SPP in their best-known foreign language (BFL), their second-best-known foreign language (SFL), and their third-best-known foreign language (TFL). The questionnaire also collected information about their age, gender, education, language background, language use, and personality traits.

The results showed that FLA was negatively correlated with SPP across all languages and contexts. The learners reported higher levels of FLA and lower levels of SPP in their TFL than in their BFL or SFL. The learners also reported higher levels of FLA and lower levels of SPP in formal contexts (such as exams or presentations) than in informal contexts (such as conversations with friends or family). The results also showed that the learners’ biographical background and personality traits influenced their FLA and SPP. The learners who started learning their BFL at an earlier age, had more exposure to it, used it more frequently, and had a higher level of education reported lower levels of FLA and higher levels of SPP in their BFL. The learners who scored higher on openness to experience, agreeableness, conscientiousness, and emotional stability reported lower levels of FLA and higher levels of SPP across all languages.

The study by Dewaele (2018) provided empirical evidence for the link between affect and cognition in multilinguals. It also demonstrated the complexity and variability of FLA and SPP depending on the learners’ language, context, and individual characteristics. The author suggested some implications for language teaching and research, such as raising awareness of the sources and effects of FLA, providing opportunities for positive feedback and self-assessment, and taking into account learners’ biographical background and personality traits when designing instruction and evaluation.

These examples illustrate how the correlational approach can provide insights into the complex interplay between cognition, conation, and affect in psychology and SLA.

Aptitude as a prediction of formal L2 learning rate

Foreign language aptitude was studied in the 1920s but saw a resurgence after World War II. The most significant development in the field occurred in 1953 when Harvard psychologist John Carroll developed the Modern Language Aptitude Test (MLAT) with a grant from the Carnegie Corporation of New York (Carroll, 1981). The MLAT is a predictive test for language learning rate in formal instruction settings and is widely used in the United States and other countries. It consists of five subtests that measure grammatical sensitivity, phonetic coding ability, and memory capacity. The long form of the test has 146 items, and the average performance score falls between 100 and 135 points. Scoring above 100 or 135 points on the MLAT indicates above-average foreign language aptitude. (Dörnyei, 2005)

Aptitude as a prediction of formal L2 learning rate refers to the idea that language aptitude, or the specific talent or potential that a person has for learning a foreign or second language (L2), can estimate how fast a person can improve their L2 proficiency in formal settings, such as classrooms or intensive courses. Language aptitude is often measured by tests that assess different aspects of language learning ability, such as phonetic coding, grammatical sensitivity, inductive learning, and rote memory. Language aptitude is considered relatively stable once a person matures and varies across individuals.

The concept of aptitude as a prediction of formal L2 learning rate emerged in the 1950s and 1960s, mainly influenced by the work of John B. Carroll and his colleagues. They developed the Modern Language Aptitude Test (MLAT), which is still widely used today. The MLAT consists of five subtests that measure different components of language aptitude:

Number learning: the ability to learn associations between numbers and foreign words
Phonetic script: the ability to identify and reproduce foreign sounds
Spelling clues: the ability to infer spelling rules from foreign words
Words in sentences: the ability to identify grammatical functions of words in sentences
Paired associates: the ability to memorize foreign words and their meanings

The MLAT was designed to measure aptitude for learning any language, regardless of its similarity or difference from the learner’s native language. The MLAT was also validated against measures of L2 learning rate in various formal settings, such as intensive military courses or college classes. The results showed that the MLAT scores were positively correlated with L2 learning rate across different languages and contexts. In other words, learners with higher aptitude scores tended to learn faster than learners with lower aptitude scores.

The concept of aptitude as prediction of formal L2 learning rate has been challenged and refined by subsequent research. Some of the current issues and debates include:

The validity and reliability of aptitude tests: How well do aptitude tests measure what they claim to measure? How consistent are aptitude test scores over time and across situations?
The specificity or generality of aptitude: Does aptitude vary depending on the language being learned and its relation to the learner’s existing linguistic knowledge? Does aptitude reflect a unique ability for language learning or a manifestation of more general cognitive abilities?
The stability or malleability of aptitude: Is aptitude a fixed trait that is determined by genetic factors and early experiences, or is it a dynamic state that environmental factors and learning strategies can influence?
The role and relevance of aptitude in different learning contexts and stages: How does aptitude affect the process and outcome of language learning in various settings (e.g., naturalistic vs. instructed; intensive vs. extensive; individual vs. collaborative)? How does it relate to different aspects of language proficiency (e.g., accuracy vs. fluency; explicit vs. implicit knowledge; receptive vs. productive skills)?

Some examples of recent studies that address these questions are:

Li (2016) conducted a study to explore the malleability of language aptitude by examining the effects of cognitive training on aptitude test scores and language learning outcomes in Chinese learners of English. He used a quasi-experimental design to compare two groups of learners who received different types of training: one group received cognitive training that targeted working memory, phonological awareness, and grammatical sensitivity, while the other group received general English training that focused on vocabulary, grammar, and reading. The study aimed to test whether cognitive training could enhance language aptitude and facilitate language learning.

The study involved 60 participants who were college students majoring in English. The participants were assigned to either the cognitive or general English training groups based on their pretest scores on the LLAMA Language Aptitude Test. The participants completed 20 sessions of training over 10 weeks, each session lasting 40 minutes. The cognitive training group used a computer program that provided adaptive exercises on working memory, phonological awareness, and grammatical sensitivity. The general English training group used a textbook that provided exercises on vocabulary, grammar, and reading. The participants also completed posttests on the LLAMA Language Aptitude Test and various measures of English proficiency (vocabulary, grammar, listening, and speaking).

The results showed that cognitive training significantly positively affected language aptitude and learning outcomes. The cognitive training group improved significantly more than the general English training group on all LLAMA Language Aptitude Test subtests, except for rote memory. The cognitive training group also improved significantly more than the general English training group on all measures of English proficiency, except for vocabulary. The results further showed that the improvement in language aptitude mediated the improvement in language proficiency. In other words, cognitive training enhanced language aptitude, which in turn facilitated language learning.

The study by Li (2016) provided empirical evidence for the malleability of language aptitude and its impact on language learning. It also demonstrated the effectiveness of cognitive training as a way to improve language aptitude and language proficiency. The author suggested some implications for language teaching and research, such as incorporating cognitive training into language instruction, designing aptitude tests that are sensitive to cognitive training effects, and exploring the mechanisms and boundary conditions of cognitive training.

Also, Granena (2013) conducted a study to investigate the specificity or generality of language aptitude by comparing the performance of high-aptitude learners on different types of tasks (linguistic vs. non-linguistic; implicit vs. explicit) in two languages (English and Spanish). He used a mixed-methods design to examine whether high-aptitude learners showed similar or different patterns of performance across tasks, languages, and modalities. The study aimed to test whether language aptitude was a domain-general or a domain-specific ability, and whether it was related to implicit or explicit learning processes.

The study involved 20 participants who were native speakers of Catalan and Spanish and who had learned English as a foreign language. The participants were selected based on their high LLAMA Language Aptitude Test scores. The participants completed four types of tasks in English and Spanish: a linguistic implicit learning task, a linguistic explicit learning task, a non-linguistic implicit learning task, and a non-linguistic explicit learning task. The tasks were presented in both oral and written modalities. The participants also completed a questionnaire that elicited their background information, language learning history, and learning preferences.

The results showed that high-aptitude learners performed well on all types of tasks in both languages and modalities, but they also showed some differences depending on the task characteristics. The results indicated that language aptitude was a domain-general ability that could be applied to both linguistic and non-linguistic domains, but it was also modulated by domain-specific factors, such as linguistic knowledge and cross-linguistic influence. The results also suggested that language aptitude was related to both implicit and explicit learning processes, but it was more strongly associated with implicit learning, especially for oral tasks.

Granena (2013) study provided empirical evidence for the complexity and variability of language aptitude and its relation to different types of tasks and languages. It also challenged the traditional view of language aptitude as a unitary and stable construct that is specific to language learning. The author suggested some implications for language teaching and research, such as developing more comprehensive and adaptive measures of language aptitude, exploring the interaction between aptitude and other individual differences and contextual factors, and investigating the neural correlates of aptitude and task performance.

Another study by Abrahamsson and Hyltenstam (2008) conducted a study to examine the role of language aptitude in ultimate attainment by comparing native-like and non-native-like L2 speakers of Swedish on various measures of aptitude and proficiency. They used a mixed-methods design to test whether nativelike adult L2 learners possessed a high degree of language aptitude that compensated for the negative effects of a critical period and whether child L2 learners attained a nativelike command of the L2 regardless of their aptitude level. The study aimed to test the validity and utility of language aptitude as a predictor of L2 learning success and as a moderator of age effects.

The study involved 195 participants who were native Spanish or Finnish speakers and had learned Swedish as an L2. The participants were divided into three groups based on their AO of L2 acquisition: early (before age 12), late (after age 12), and very late (after age 17). The participants completed a battery of tests that measured their aptitude and L2 proficiency. The tests included the Modern Language Aptitude Test (MLAT), the LLAMA Language Aptitude Test, and various tests of L2 knowledge and skills (vocabulary, grammar, pronunciation, listening, reading, writing, and speaking).

The results showed that aptitude was a strong predictor of L2 proficiency across all groups, but it also interacted with AO in different ways. The results indicated that nativelike adult L2 learners had exceptionally high aptitude scores that enabled them to overcome the maturational constraints on L2 acquisition. The results also suggested that child L2 learners showed some aptitude effects on their L2 proficiency, especially on their pronunciation and grammar skills. The results further revealed that non-native-like adult L2 learners had lower aptitude scores than nativelike adult L2 learners, but higher aptitude scores than child L2 learners.

The study by Abrahamsson and Hyltenstam (2008) provided empirical evidence for the robustness and relevance of language aptitude in near-native L2 acquisition. It also challenged the assumption that child L2 learners are immune to aptitude effects and that adult L2 learners are doomed to non-nativelikeness. The authors suggested some implications for language teaching and research, such as identifying and nurturing high-aptitude learners, developing more sensitive and comprehensive measures of language aptitude, and exploring the neural correlates of aptitude and proficiency.

Finally, Wen et al. (2017) conducted a study to propose a working memory perspective on language aptitude, arguing that working memory capacity is a key factor underlying various aptitude components and influences language learning outcomes. They used a theoretical and empirical approach to examine how working memory relates to different aspects of language aptitude and language acquisition, such as phonological coding, grammatical sensitivity, inductive learning, rote memory, implicit learning, explicit learning, and ultimate attainment. The study aimed to provide a comprehensive and coherent framework for understanding and measuring language aptitude from a working memory perspective.

The study involved a review of previous literature on working memory and language aptitude and an analysis of empirical data from several studies conducted by the authors and their colleagues. The data included measures of working memory (such as operation span, symmetry span, reading span, and listening span), language aptitude (such as the Modern Language Aptitude Test and the LLAMA Language Aptitude Test), and language proficiency (such as vocabulary, grammar, pronunciation, listening, reading, writing, and speaking) in various languages (such as English, Spanish, French, Chinese, and Arabic).

The results showed that working memory was closely related to language aptitude and language acquisition in multiple ways. The results indicated that working memory was a central component of language aptitude that underlay various subcomponents of aptitude, such as phonological coding, grammatical sensitivity, inductive learning, and rote memory. The results also suggested that working memory was involved in both implicit and explicit learning processes of language acquisition, but it was more strongly associated with implicit learning than explicit learning. The results further revealed that working memory was a predictor of language proficiency and ultimate attainment in different languages and modalities.

The study by Wen et al. (2017) provided theoretical and empirical evidence for the working memory perspective on language aptitude. It also challenged the traditional view of language aptitude as a unitary and stable construct that is specific to language learning. The authors suggested some implications for language teaching and research, such as developing more comprehensive and adaptive measures of language aptitude based on working memory, exploring the interaction between working memory and other individual differences and contextual factors, and investigating the neural correlates of working memory and language aptitude.

These studies illustrate the diversity and complexity of language aptitude theory and research and the challenges and opportunities for future development.

Research has shown that aptitude strongly predicts success in formal L2 learning. Aptitude can be defined as “an individual’s potential for learning or acquiring knowledge, skills or abilities” (Skehan, 1989, p. 2). Language aptitude, specifically, has been shown to be a key factor in predicting the rate of L2 learning. Carroll and Sapon (1959) developed the Modern Language Aptitude Test (MLAT), which measures different components of language aptitude, such as phonetic coding ability, grammatical sensitivity, and inductive language learning ability. The results of the MLAT have been shown to be a strong predictor of success in formal L2 learning (Skehan, 1991).

For example, Skehan (1991) conducted a study in which he administered the MLAT to a group of learners studying English as a foreign language. He found that the learners’ MLAT scores significantly predicted their L2 proficiency and that learners with higher language aptitude made faster progress in their L2 than those with lower aptitude. Similarly, Robinson (2002) conducted a study examining the relationship between language aptitude and the acquisition rate of grammatical features in Spanish. He found that learners with higher language aptitude were able to acquire grammatical features more quickly than those with lower aptitude.

Furthermore, Dörnyei and Skehan (2003) conducted a meta-analysis of 39 studies on the relationship between language aptitude and L2 learning. They found that language aptitude was a significant predictor of success in formal L2 learning, regardless of the language or the type of instruction used. However, it is important to note that aptitude is not the only factor that influences L2 learning. Other factors, such as motivation and opportunity for language use, also play a role in determining the rate of L2 learning (Dörnyei, 2005).

Language aptitude has been shown to be a strong predictor of success in formal L2 learning. Tests such as the MLAT measure different components of language aptitude and can help predict the rate of L2 learning. However, aptitude is not the only factor that influences L2 learning, and other factors such as motivation and opportunity for language use, should also be considered.

Lack of L2 aptitudes or general language-related difficulties?

Some language learners may struggle with acquiring a second language, and it may not necessarily be due to a lack of effort or motivation. In some cases, it may be due to a lack of L2 aptitude, which refers to the “innate, natural ability to learn a foreign language” (Dörnyei, 2005, p. 118). However, it can be difficult to distinguish between lack of L2 aptitude and more general language-related difficulties, such as difficulty with phonological processing or working memory.

Some researchers have attempted to develop tools to measure L2 aptitude, such as the Modern Language Aptitude Test (MLAT) developed by Carroll and Sapon (1959). However, these tests may not always accurately distinguish between lack of L2 aptitude and other language-related difficulties (Dörnyei & Skehan, 2003). In addition, some argue that aptitude is not an innate ability but rather a combination of various cognitive and affective factors, including motivation and learning strategies (Dörnyei, 2005).

Furthermore, it is important to note that even individuals with a lack of L2 aptitude can still learn a second language with sufficient effort and effective learning strategies (Robinson, 2002). For example, an individual with difficulty with phonological processing may struggle with pronunciation but may still be able to develop strong skills in reading and writing.

Lack of L2 aptitude, or general language-related difficulties, refers to the idea that some learners may have low or limited potential for learning a second or foreign language (L2), either because they lack specific cognitive or perceptual abilities that are advantageous for L2 acquisition, or because they have more general difficulties with language processing or communication. This idea has implications for understanding and addressing individual differences in L2 learning outcomes and experiences.

L2 aptitude is a concept that refers to the specific talent or potential that a person has for learning a L2. It is often measured by formal tests that assess different aspects of language learning ability, such as phonetic coding, grammatical sensitivity, inductive learning, and rote memory. L2 aptitude is thought to be relatively stable once a person matures, and to vary across individuals (Carroll, 1981). L2 aptitude is also thought to predict the rate and level of L2 learning success, especially in formal and intensive settings (Doughty et al., 2010).

Some learners may have low L2 aptitude scores, indicating that they have less potential for L2 learning than others. This may be due to various factors, such as genetic predisposition, early experiences, cognitive style, motivation, or affective state. Low L2 aptitude may result in slower or lower L2 learning outcomes and more difficulties or challenges in L2 learning processes. For example, learners with low phonetic coding ability may have trouble perceiving and producing L2 sounds accurately; learners with low grammatical sensitivity may have trouble identifying and applying L2 rules correctly; learners with low inductive learning ability may have trouble inferring and generalizing L2 patterns from input; and learners with low rote memory ability may have trouble memorizing and recalling L2 words and phrases.

However, low L2 aptitude does not necessarily mean that a learner cannot learn a L2 at all. It may mean that the learner needs more time, effort, practice, feedback, or support to achieve their L2 learning goals. It may also mean that the learner needs to adopt different strategies, methods, or techniques to enhance their L2 learning potential. For example, learners with low phonetic coding ability may benefit from using visual aids, such as charts or diagrams, to learn L2 sounds; learners with low grammatical sensitivity may benefit from using explicit instruction or metalinguistic feedback to learn L2 rules; learners with low inductive learning ability may benefit from using analogies or examples to learn L2 patterns; and learners with low rote memory ability may benefit from using mnemonics or associations to learn L2 words and phrases.

Some learners may also have general language-related difficulties that affect their L2 learning potential. These difficulties may not be specific to L2 aptitude components, but rather to broader aspects of language processing or communication. For example, some learners may have dyslexia, which is a difficulty with reading and spelling words; some learners may have dysgraphia, which is a difficulty with writing words; some learners may have dyscalculia, which is a difficulty with numbers and calculations; some learners may have aphasia, which is a difficulty with language production or comprehension due to brain damage; some learners may have autism spectrum disorder (ASD), which is a difficulty with social communication and interaction; and some learners may have attention deficit hyperactivity disorder (ADHD), which is a difficulty with attention and impulse control.

These general language-related difficulties may also result in slower or lower L2 learning outcomes and more difficulties or challenges in L2 learning processes. For example, learners with dyslexia may have trouble decoding and encoding written texts in the L2; learners with dysgraphia may have trouble forming and organizing written texts in the L2; learners with dyscalculia may have trouble understanding and applying numerical concepts in the L2; learners with aphasia may have trouble producing or comprehending spoken texts in the L2; learners with ASD may have trouble interpreting and expressing pragmatic meanings in the L2; and learners with ADHD may have trouble focusing and regulating their behavior in the L2.

However, these general language-related difficulties do not necessarily mean that a learner cannot learn a L2 at all either. They may mean that the learner needs more specialized intervention, adaptation, or accommodation to achieve their L2 learning goals. They may also mean that the learner needs to leverage their strengths, interests, or preferences to enhance their L2 learning potential. For example, learners with dyslexia may benefit from using audio or visual materials to learn the L2 (Wen et al., 201

7); learners with dysgraphia may benefit from using speech recognition or word prediction software to write in the L2 (Wen, 2016); learners with dyscalculia may benefit from using concrete or visual representations of numbers in the L2 (Granena, 2013); learners with aphasia may benefit from using gestures or pictures to communicate in the L2 (Wen & Skehan, 2021); learners with ASD may benefit from using explicit or structured instruction to learn the L2 (Doughty et al., 2010); and learners with ADHD may benefit from using interactive or engaging activities to learn the L2 (Wen et al., 2017).

In short, lack of L2 aptitude, or general language-related difficulties, may pose some challenges for L2 learners, but they do not necessarily prevent them from learning a L2. With appropriate assessment, intervention, adaptation, and accommodation, L2 learners can overcome or compensate for their difficulties and achieve their L2 learning goals. Moreover, with positive motivation, attitude, and affect, L2 learners can enjoy and appreciate their L2 learning experiences.

Memory capacity as a privileged component of L2 aptitude

Memory capacity has been identified as a crucial component of foreign language aptitude. As defined by Carroll and Sapon (1959), aptitude refers to “an individual’s potential for learning or acquiring knowledge” (p. 5). Memory capacity, in particular, has been found to play a privileged role in L2 aptitude, as it is strongly associated with the ability to retain and retrieve new language information (Skehan, 1998).

One of the most influential theories on the role of memory in L2 learning is the working memory model proposed by Baddeley and Hitch (1974). According to this model, working memory is a limited-capacity system that is responsible for temporary storage and processing of information. The model consists of several components: a central executive, a phonological loop, and a visuospatial sketchpad. The phonological loop is particularly important for language learning, as it is responsible for storing and manipulating auditory information, such as speech sounds and words.

Research has consistently shown that working memory capacity is strongly related to L2 learning outcomes, and that it may even predict success in language learning better than other aptitude measures (Skehan, 1991; Wen et al., 2017). For example, Wen et al. (2017) proposed that working memory capacity underlies various components of foreign language aptitude, including phonetic coding ability, grammatical sensitivity, and inductive language learning ability. They found that individuals with higher working memory capacity tended to perform better on these aptitude components, and were also more successful in L2 learning overall.

Furthermore, research has shown that working memory capacity is malleable, and that training can lead to improvements in this area (e.g. Weskamp & Friederici, 2018). This suggests that interventions aimed at improving working memory capacity could be effective in enhancing L2 learning outcomes, particularly for individuals who may struggle with memory-related aspects of language learning.

Memory capacity as a privileged component of L2 aptitude refers to the idea that the ability to store and process information simultaneously in real time is a crucial factor that influences L2 learning outcomes and experiences. This idea is based on the notion of working memory, which is a cognitive system that allows us to maintain and manipulate a limited amount of task-relevant information in our immediate consciousness in order to complete cognitive tasks in everyday life (Schwieter & Wen, 2021). This idea has implications for understanding and measuring L2 aptitude from a working memory perspective.

L2 aptitude is a concept that refers to the specific talent or potential that a person has for learning a L2. It is often measured by formal tests that assess different aspects of language learning ability, such as phonetic coding, grammatical sensitivity, inductive learning, and rote memory. However, these traditional tests have been criticized for being too narrow, static, and context-independent, and for ignoring the role of other cognitive abilities that are involved in L2 learning, such as working memory (Wen et al., 2017).

Working memory is a concept that refers to the specific capacity or potential that a person has for storing and processing information simultaneously in real time. It is often measured by complex span tasks that require storing and processing information, such as reading, listening, operation, and symmetry. Working memory is thought to be relatively dynamic, flexible, and context-dependent, and to play a key role in various cognitive domains, such as language processing, reasoning, problem-solving, and learning (Baddeley, 2000).

Some learners may have high working memory capacity, indicating that they have more potential for storing and processing information simultaneously in real time than others. This may be due to various factors, such as genetic predisposition, early experiences, cognitive style, motivation, or affective state. High working memory capacity may result in faster or higher L2 learning outcomes and more ease or efficiency in L2 learning processes. For example, learners with high working memory capacity may have an advantage in perceiving and producing L2 sounds accurately; identifying and applying L2 rules correctly; inferring and generalizing L2 patterns from input; memorizing and recalling L2 words and phrases; comprehending and producing L2 texts; and acquiring implicit and explicit L2 knowledge (Wen et al., 2017).

However, high working memory capacity does not necessarily mean that a learner will learn a L2 effortlessly or perfectly. It may mean that the learner can cope better with the cognitive demands of L2 learning tasks than others. It may also mean that the learner can optimize their working memory capacity by using appropriate strategies, methods, or techniques to enhance their L2 learning potential. For example, learners with high working memory capacity may benefit from using chunking or grouping strategies to reduce the load on their working memory; using rehearsal or elaboration strategies to enhance the retention of information in their working memory; using attentional or metacognitive strategies to regulate the allocation of resources in their working memory; and using transfer or integration strategies to link the information in their working memory with their prior knowledge or long-term memory (Wen et al., 2017).

Some learners may also have low working memory capacity, affecting their L2 learning potential. These learners may face more challenges or difficulties in storing and processing information simultaneously in real time than others. For example, learners with low working memory capacity may have trouble perceiving and producing L2 sounds accurately; identifying and applying L2 rules correctly; inferring and generalizing L2 patterns from input; memorizing and recalling L2 words and phrases; comprehending and producing L2 texts; and acquiring implicit and explicit L2 knowledge (Wen et al., 2017).

However, low working memory capacity does not necessarily mean that a learner cannot learn a L2 at all. It may mean that the learner needs more time, effort, practice, feedback, or support to achieve their L2 learning goals. It may also mean that the learner needs to adopt different strategies, methods, or techniques to enhance their L2 learning potential. For example, learners with low working memory capacity may benefit from using visual aids, such as charts or diagrams, to learn L2 sounds; using explicit instruction or metalinguistic feedback to learn L2 rules; using analogies or examples to learn L2 patterns; using mnemonics or associations to learn L2 words and phrases; using scaffolding or cooperative learning to comprehend and produce L2 texts; and using explicit instruction or corrective feedback to acquire implicit and explicit L2 knowledge (Wen et al., 2017).

Harrington and Sawyer (1992) conducted a study in the context of advanced L2 learners of English with various native languages. The study aimed to examine the relationship between working memory capacity and L2 reading skills. They used a reading span test (Daneman & Carpenter, 1980) as an index of working memory capacity, which required the participants to read sentences aloud and recall each sentence’s last word in order. The sample consisted of 60 L2 learners from various countries who were enrolled in an intensive English program at a university in Japan. They also administered two measures of reading skill: a TOEFL reading comprehension test and a cloze test. They measured the scores on these tests and calculated the correlations among them. They found that working memory capacity, as measured by the reading span test, correlated highly with reading skill measures, accounting for 30% of the variance in TOEFL scores and 25% in cloze scores. They also found that passive short-term memory measures, such as digit span and word span tests, did not correlate strongly with reading skill. They concluded that working memory capacity reflects the ability to store and process information simultaneously in real time, and that this ability is crucial for skilled L2 reading.

However, Juffs (2004) conducted a study in the context of adult L2 learners of English with different native languages. The study aimed to investigate individual differences in online processing of ambiguous L2 sentences and whether working memory capacity affects L2 sentence processing. The sample consisted of 46 Spanish-speaking participants, 46 Chinese-speaking participants, and 46 native English speakers. He used two working memory measures: a reading span test and a nonword repetition test. He also used a self-paced reading task with sentences containing relative subject-extracted or object-extracted clauses. He measured the reading times and accuracy of comprehension questions for each sentence. He analyzed the data using ANOVAs and regression analyses. He found that working memory measures did not predict the reading times or accuracy of either type of sentences. He also found that L2 learners showed similar patterns of processing difficulty as native speakers, but with longer reading times and lower accuracy. He concluded that working memory does not play a significant role in L2 sentence processing, and that L2 learners have intact grammatical representations but slower access to them.

In conclusion, memory capacity as a privileged component of L2 aptitude refers to the idea that working memory is a crucial factor that influences L2 learning outcomes and experiences. Working memory is a cognitive system that allows us to store and process information simultaneously in real time. Working memory capacity varies across individuals and affects various aspects of L2 learning ability. Complex span tasks can measure working memory capacity and can be enhanced by appropriate strategies, methods, or techniques. Working memory capacity can also interact with other cognitive abilities and contextual factors in L2 learning.

The Contribution of Memory to Aptitudes

Memory is one of the cognitive abilities that contributes to aptitude, which is the innate or acquired potential to learn a new skill or domain of knowledge. Memory can be divided into different types, such as short-term, working, and long-term, each of which plays a different role in learning and performance.

Short-term memory is the ability to hold a small amount of information in mind for a brief period of time, such as remembering a phone number or a list of words. Short-term memory is often measured by simple span tasks, such as digit span or word span, which require the participants to repeat a series of digits or words in the same order as they were presented. Short-term memory is important for learning because it allows us to retain the information that we encounter in our environment until we can process it further or store it in long-term memory. For example, when we learn new vocabulary or phonology in a L2, we need to keep the new words or sounds in our short-term memory until we can associate them with their meanings or rules (Baddeley et al., 1998). However, short-term memory has a limited capacity and duration, which means that we can only remember a few items at a time and for a few seconds unless we rehearse them. Therefore, short-term memory alone is insufficient for learning complex or abstract concepts requiring deeper processing or integration with prior knowledge.

Working memory is the ability to store and manipulate information simultaneously in real-time, such as solving a math problem or comprehending a sentence. Working memory is often measured by complex span tasks, such as reading span or operation span, which require the participants to perform two tasks at the same time: processing some information (such as reading sentences or solving equations) and remembering some other information (such as the last word of each sentence or the result of each equation). Working memory is crucial for learning because it allows us to perform cognitive tasks involving multiple steps or analysis levels. For example, when we read a text or listen to a speech in an L2, we need to use our working memory to decode the words and sentences, activate their meanings and structures, integrate them with the context and our background knowledge, and infer their implications and intentions (Wen et al., 2021). Working memory also enables us to monitor and regulate our own learning processes and strategies, such as checking our comprehension or applying feedback (Dörnyei & Ryan, 2015). However, working memory also has a limited capacity and duration, which means that we can only process and remember a certain amount of information at a time and for a certain period of time. Therefore, working memory is affected by factors such as task difficulty, attentional control, interference, or anxiety (Barrouillet & Camos, 2012).

Long-term memory is the ability to store and retrieve information over a long period of time, such as recalling facts or events from the past. Long-term memory can be divided into different types, such as declarative memory and procedural memory. Declarative memory is the memory for factual knowledge that can be consciously accessed and verbally expressed such as declarative memory and procedural memory. Declarative memory is the memory for factual knowledge that can be consciously accessed and verbally expressed, such as names, dates, or definitions. Procedural memory is the memory for skills or habits that are acquired through practice and performed automatically without conscious awareness, such as riding a bike or playing an instrument. Long-term memory is essential for learning because it allows us to accumulate and organize the information that we have learned over time and use it for various purposes. For example, when we learn grammar or pragmatics in an L2, we need to use our declarative memory to store the rules or conventions that govern the language use and our procedural memory to apply them fluently and appropriately in different situations (Ullman, 2016). Long-term memory has a large capacity and duration, which means that we can store and remember a lot of information for a long time. However, long-term memory is not always accurate or reliable, which means that we may forget some information over time or distort some information due to biases or errors (Schacter et al., 2011).

Memory is related to aptitude in various ways, depending on the type of memory and the domain of learning. Several studies have shown that memory measures can predict aptitude or achievement in domains such as L2 learning, math, or music. For instance, Wen (2016) reviewed the literature on working memory and L2 learning and found that working memory capacity was positively correlated with various aspects of L2 proficiency, such as vocabulary, grammar, reading, listening, speaking, and writing. He also proposed a working memory model that integrated different components and executive functions relevant for L2 learning. Similarly, Alloway and Passolunghi (2011) examined the relationship between working memory, IQ, and math skills in children and found that working memory was a better predictor of math skills than IQ. They also suggested that working memory was involved in different processes of math learning, such as counting, arithmetic, problem-solving, and reasoning. Moreover, Ruthsatz et al. (2008) investigated the role of working memory and other cognitive factors in musical expertise and found that working memory was the only factor that distinguished between expert and novice musicians. They also argued that working memory was important for musical performance because it enabled musicians to encode, store, and manipulate musical information in real-time.

However, memory is not a unitary construct and its role may vary depending on the task, the learner, and the context. Therefore, it is important to consider the specific aspects of memory that are relevant for a particular domain of aptitude and how they interact with other cognitive and environmental factors. For example, some studies have found that different types of memory may have different effects on L2 learning outcomes depending on the type of L2 input or instruction. Juffs (2004) compared the effects of working memory and declarative memory on L2 sentence processing among adult L2 learners with different native languages. He found that working memory did not predict the reading times or accuracy of ambiguous L2 sentences, whereas declarative memory did. He concluded that working memory did not play a significant role in L2 sentence processing, and that L2 learners had intact grammatical representations but slower access to them. On the other hand, Ameringer (2018) examined the effects of working memory and declarative memory on L2 aptitude among workers and students with different levels of education. She found that declarative memory predicted L2 aptitude, whereas working memory did not. She suggested that declarative memory was more important for L2 aptitude because it reflected the ability to store and retrieve L2 knowledge, whereas working memory was more important for L2 performance because it reflected the ability to process and manipulate L2 information.

In brief, memory is one of the cognitive abilities that contribute to aptitude, which is the innate or acquired potential to learn a new skill or domain of knowledge. Memory can be divided into different types, such as short-term, working, and long-term, each of which plays a different role in learning and performance. Memory is related to aptitude in various ways, depending on the type of memory and the domain of learning. Several studies have shown that memory measures can predict aptitude or achievement in domains such as L2 learning, math, or music. However, memory is not a unitary construct and its role may vary depending on the task, the learner, and the context. Therefore, it is important to consider the specific aspects of memory that are relevant for a particular domain of aptitude and how they interact with other cognitive and environmental factors.

Aptitude and age

According to many researchers in Second Language Acquisition (SLA), young children have a greater ability to learn their first language entirely implicitly due to their cognitive and linguistic endowment. However, when learning a second language, adolescents and adults may struggle to achieve complete success because they rely on explicit learning strategies involving analysis and analogy. This idea is known as the Fundamental Difference Hypothesis, first proposed by Bley-Vroman in 1990. The hypothesis suggests that late-starting learners’ success in learning a second language will depend on their analytical capacities for explicit learning and their memory for implicit learning. In contrast, children are more likely to rely on innate language learning mechanisms, resulting in uniform development of their first language competence.

This hypothesis also suggests that individual differences, including aptitude, should mainly matter when learning a second language after a certain age. However, the question remains whether individual differences also play a role in young L2 learners. Some researchers have suggested that even in young L2 learners, individual differences such as memory capacity and cognitive abilities can significantly impact their language learning outcomes (Skehan, 1989).

For instance, a study by Golestani, Price, and Scott (2011) examined the role of individual differences in young adult L2 learners. They found that individual differences in cognitive control, as measured by a Stroop task, significantly predicted the participants’ ability to learn a grammar rule in a new language. Another study by Hartshorne, Tenenbaum, and Pinker (2018) suggested that individual differences in nonverbal IQ, working memory, and cognitive flexibility can predict the rate of L2 acquisition in young children.

Furthermore, a study by Gómez, Berent, and Benavides-Varela (2014) found that phonological memory, a component of working memory, was a significant predictor of Spanish vocabulary acquisition in both children and adults. These findings suggest that individual differences, such as memory capacity, cognitive control, and cognitive flexibility, can play a crucial role in young L2 learners’ success in acquiring a second language.

Aptitude is the innate or acquired potential to learn a new skill or domain of knowledge. Factors such as cognitive abilities, motivation, personality, learning styles, and environmental conditions can influence aptitude. One of the factors that has received much attention in the literature is age, which refers to the chronological or biological age of the learner. Age is often considered as a determinant of aptitude, especially in the domain of second language (L2) learning. In this essay, I will discuss how age affects aptitude in different ways, depending on the type of aptitude and the stage of learning. I will also review some empirical studies examining the relationship between age and aptitude in L2 learning and other domains. Finally, I will address some of the limitations and implications of the research on age and aptitude.

Age can affect aptitude in different ways, depending on the type of aptitude and the stage of learning. One way to classify aptitude is to distinguish between general aptitude and specific aptitude. General aptitude refers to the overall ability to learn any skill or domain of knowledge, whereas specific aptitude refers to the ability to learn a particular skill or domain of knowledge (Carroll & Sapon, 1959). General aptitude is often measured by intelligence tests or cognitive tests that assess various aspects of mental abilities, such as reasoning, memory, attention, and processing speed. Specific aptitude is often measured by tests that assess the knowledge or skills related to a specific domain, such as language, math, or music.

Age can affect general aptitude in different ways at different stages of life. Generally speaking, general aptitude tends to increase during childhood and adolescence, reach a peak in early adulthood, and decline gradually in later adulthood (Salthouse et al., 2004). This pattern reflects the changes in brain development and function that occur across the lifespan. During childhood and adolescence, the brain undergoes rapid growth and maturation, which enhances cognitive abilities and learning potential. During early adulthood, the brain reaches its optimal efficiency and plasticity level, enabling high performance and adaptation. During later adulthood, the brain experiences gradual deterioration and degeneration, which impairs cognitive abilities and learning potential.

However, age does not uniformly affect general aptitude across all mental abilities. Some aspects of general aptitude may decline earlier or faster than others due to different rates of aging or environmental influences. For example, fluid intelligence, which refers to the ability to solve novel problems using logic and reasoning, may decline earlier or faster than crystallized intelligence, which refers to the ability to use accumulated knowledge and experience (Horn & Cattell, 1967). Similarly, processing speed, which refers to the ability to perform simple mental operations quickly and accurately, may decline earlier or faster than working memory, which refers to the ability to store and manipulate information simultaneously in real time (Salthouse et al., 2004). Moreover, some aspects of general aptitude may be more susceptible or resistant to environmental influences than others due to different levels of modifiability or stability. For example, attention, which refers to the ability to focus on relevant information and ignore irrelevant information, may be more susceptible to environmental influences such as distraction, stress, or fatigue than memory, which refers to the ability to store and retrieve information over time (Baddeley et al., 2009).

Age can also affect specific aptitude in different ways at different stages of learning. One domain that has been extensively studied in relation to age and aptitude is L2 learning. L2 learning refers to the process of acquiring a language other than one’s native language. L2 learning can be influenced by various factors, such as motivation, personality, learning styles, and environmental conditions. However, one of the most debated factors is age, which refers to the age at which one starts or finishes L2 learning. Age can affect L2 aptitude in different ways depending on the type of L2 aptitude and the stage of L2 learning.

One way to classify L2 aptitude is to distinguish between ultimate attainment and rate of learning. Ultimate attainment refers to the level of proficiency or competence that one can achieve in a L2 after a long period of exposure or instruction. Rate of learning refers to the speed or efficiency with which one can acquire a L2 in a given amount of time or with a given amount of input. Ultimate attainment and rate of learning are often measured by tests that assess various aspects of L2 knowledge or skills, such as vocabulary, grammar, pronunciation, comprehension, or production.

Age can affect ultimate attainment and rate of learning in different ways at different stages of L2 learning. Generally speaking, ultimate attainment tends to decrease with increasing age of onset (AO), which refers to the age at which one starts L2 learning. This pattern reflects the critical period hypothesis (CPH), which proposes that there is a biologically determined window of opportunity for optimal L2 learning that closes around puberty (Lenneberg, 1967). According to the CPH, early starters (those who start L2 learning before puberty) have an advantage over late starters (those who start L2 learning after puberty) in achieving native-like proficiency or competence in a L2. This advantage is especially evident in aspects of L2 that are more dependent on implicit or subconscious learning processes, such as phonology or syntax (Birdsong, 2006).

Age can also affect rate of learning in different ways at different stages of L2 learning. Generally speaking, rate of learning tends to increase with increasing age of learning (AL), which refers to the age at which one is exposed to or instructed in an L2. This pattern reflects the cognitive development hypothesis (CDH), which proposes that there is a positive correlation between cognitive development and L2 learning ability (Singleton, 2005). According to the CDH, older learners (those who are exposed to or instructed in an L2 after puberty) have an advantage over younger learners (those who are exposed to or instructed in an L2 before puberty) in acquiring an L2 in a given amount of time or with a given amount of input. This advantage is especially evident in aspects of L2 that are more dependent on explicit or conscious learning processes, such as vocabulary or pragmatics (Muñoz & Singleton, 2011).

However, rate of learning does not always increase with increasing AL across all aspects of L2 or across all learners. Some aspects of L2 that are more dependent on implicit or subconscious learning processes, such as phonology or syntax, may not be affected by AL or may even benefit from earlier AL due to the advantages of neural plasticity or perceptual sensitivity (DeKeyser et al., 2010). Similarly, some learners who are exposed to or instructed in an L2 before puberty may acquire an L2 faster than those who are exposed to or instructed in an L2 after puberty due to individual differences in motivation, personality, learning styles, or environmental conditions (Muñoz & Singleton, 2011).

Age is one of the factors that affects aptitude, which is the innate or acquired potential to learn a new skill or domain of knowledge. Age can affect aptitude in different ways, depending on the type of aptitude and the stage of learning. One domain that has been extensively studied in relation to age and aptitude is L2 learning. Various factors, such as cognitive abilities, motivation, personality, learning styles, and environmental conditions can influence L2 learning. However, one of the most debated factors is age, which refers to the chronological or biological age of the learner. Age can affect L2 aptitude in different ways depending on the type of L2 aptitude and the stage of L2 learning. One way to classify L2 aptitude is to distinguish between ultimate attainment and rate of learning. Ultimate attainment refers to the level of proficiency or competence that one can achieve in an L2 after a long period of exposure or instruction. Rate of learning refers to the speed or efficiency with which one can acquire an L2 in a given amount of time or with a given amount of input. Age can affect ultimate attainment and rate of learning in different ways at different stages of L2 learning. Generally speaking, ultimate attainment tends to decrease with increasing age of onset (AO), which refers to the age at which one starts L2 learning. This pattern reflects the critical period hypothesis (CPH), which proposes that there is a biologically determined window of opportunity for optimal L2 learning that closes around puberty.

However, ultimate attainment does not always decrease with increasing AO across all aspects of L2 or across all learners. Some aspects of L2 that are more dependent on explicit or conscious learning processes, such as vocabulary or pragmatics, may not be affected by AO or may even benefit from later AO due to the advantages of cognitive maturity or metalinguistic awareness. Similarly, some learners who start L2 learning after puberty may achieve native-like proficiency or competence in a L2 due to individual differences in motivation, personality, learning styles, or environmental conditions. Age can also affect rate of learning in different ways at different stages of L2 learning. Generally speaking, rate of learning tends to increase with increasing age of learning (AL), which refers to the age at which one is exposed to or instructed in an L2. This pattern reflects the cognitive development hypothesis (CDH), which proposes that there is a positive correlation between cognitive development and L2 learning ability. However, rate of learning does not always increase with increasing AL across all aspects of L2 or across all learners. Some aspects of L2 that are more dependent on implicit or subconscious learning processes, such as phonology or syntax, may not be affected by AL or may even benefit from earlier AL due to the advantages of neural plasticity or perceptual sensitivity. Similarly, some learners exposed to or instructed in an L2 before puberty may acquire an L2 faster than those exposed to or instructed in an L2 after puberty due to individual differences in motivation, personality, learning styles, or environmental conditions.

Multidimensional aptitudes

In recent years, researchers have been increasingly interested in exploring the multidimensionality of language aptitude. While early research on language aptitude focused on identifying a single, underlying factor that could explain individual differences in L2 learning, more recent studies suggest that language aptitude may be better understood as a set of separate, but related, components. This perspective has been labeled the “multidimensional” approach to language aptitude (Skehan, 2018).

The multidimensional approach posits that language aptitude is composed of several distinct cognitive abilities, including working memory capacity, phonological memory, grammatical sensitivity, and inductive learning ability (Golestani, Price, & Scott, 2011). Working memory capacity refers to the ability to temporarily store and manipulate information in the mind, while phonological memory involves the ability to remember and reproduce sounds and sound sequences. Grammatical sensitivity involves the ability to recognize and use the rules of grammar in a language, while inductive learning ability refers to the ability to extract and generalize patterns from input data (Gómez, Berent, & Benavides-Varela, 2014).

Research on multidimensional language aptitude has shown that these separate components are related to different aspects of L2 learning. For example, working memory capacity has been found to be particularly important for learning vocabulary and syntax (Skehan, 1989), while phonological memory appears to be important for acquiring pronunciation and intonation (Golestani et al., 2011). Grammatical sensitivity, on the other hand, is closely related to the ability to learn and produce grammatical structures in a new language (Hartshorne, Tenenbaum, & Pinker, 2018), and inductive learning ability has been found to be particularly important for learning vocabulary and grammar in a more implicit, naturalistic way (Gómez et al., 2014).

The multidimensional approach to language aptitude has important language teaching and learning implications. For example, it suggests that language learners may benefit from training specifically targeting each of the separate components of language aptitude. For instance, exercises designed to improve working memory capacity may help learners better retain and manipulate new vocabulary and grammatical structures, while exercises focused on phonological memory may help learners better recognize and reproduce the sounds of a new language (Skehan, 2018).

Another implication of the multidimensional approach to language aptitude is that individual learners may have different strengths and weaknesses across the different components of language aptitude. For example, one learner may have a strong working memory but a weak phonological memory, while another learner may have the opposite profile. This suggests that language teachers may need to tailor their teaching methods to the specific aptitude profiles of individual learners, in order to maximize their learning potential (Skehan, 2018).

The multidimensional approach to language aptitude represents a significant shift in the way researchers and language teachers understand individual differences in L2 learning. By recognizing that language aptitude is composed of separate, but related, cognitive components, researchers can better understand how individual learners acquire and use a new language. This approach has important implications for language teaching and learning, and suggests that teachers may need to tailor their teaching methods to the specific aptitude profiles of individual learners, in order to help them reach their full potential.

The future of L2 aptitude

Language aptitude is a complex construct that refers to the cognitive and perceptual abilities that facilitate second language (L2) learning and processing. It has been a topic of interest for researchers and educators for more than six decades, since the development of the first aptitude tests in the 1950s (Carroll & Sapon, 1959). However, the concept of aptitude has evolved over time, as new theoretical frameworks and empirical findings have emerged in the fields of second language acquisition (SLA), cognitive psychology, and neuroscience.

One of the major developments in L2 aptitude research has been the shift from a static to a dynamic view of aptitude. Traditionally, aptitude was seen as a fixed trait that determined the rate and ultimate level of L2 learning, regardless of the learning context or the learner’s motivation and effort (Carroll, 1981). However, more recent research has challenged this view and suggested that aptitude is not a unitary ability but a complex of abilities that are sensitive to the type and stage of L2 learning and processing (Dörnyei & Ryan, 2015; Robinson, 2005). For example, different aptitude components may be more or less relevant for implicit or explicit learning, for incidental or intentional learning, for input-based or output-based tasks, and for beginner or advanced learners (DeKeyser & Koeth, 2011; Granena & Long, 2013; Robinson et al., 2012). Moreover, aptitude may not be immutable but malleable, as it can be influenced by experience and training (Li et al., 2014; Sasaki, 2011; Wen et al., 2017). Therefore, aptitude should be seen as a dynamic construct that interacts with other individual differences and contextual factors in L2 learning and processing.

Another major development in L2 aptitude research has been the integration of cognitive psychology and neuroscience perspectives. These perspectives have provided new insights into the cognitive mechanisms and neural correlates of L2 aptitude components and functions. For example, cognitive psychology has identified working memory, attentional control, phonological short-term memory, declarative memory, procedural memory, analogical reasoning, pattern recognition, and statistical learning as some of the key abilities involved in L2 learning and processing (Doughty et al., 2010; Linck et al., 2013; Skehan, 2002). Neuroscience has revealed how these abilities are associated with different brain structures and networks, such as the prefrontal cortex, the hippocampus, the basal ganglia, the cerebellum, and the left inferior frontal gyrus (Abutalebi et al., 2015; Wong et al., 2019). These perspectives have also enabled the use of new methods and tools to measure aptitude components and functions more directly and objectively, such as computerized tasks, eye-tracking devices, electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS) (Granena & Long, 2013; Tagarelli et al., 2015; Wong et al., 2019).

However, despite these developments, there are still some challenges and limitations in L2 aptitude research. One of them is the lack of consensus on defining and operationalizing aptitude components and functions. Different researchers have used different terms and labels to refer to similar or overlapping abilities (e.g., language analytic ability vs. grammatical sensitivity vs. language analysis vs. language awareness) or to different aspects of the same ability (e.g., working memory capacity vs. working memory span vs. working memory updating) (Dörnyei & Ryan, 2015; Linck et al., 2013). Moreover, different researchers have used different tasks and tests to measure these abilities, which may vary in their validity and reliability (DeKeyser & Koeth, 2011; Granena & Long, 2013). Therefore, there is a need for more clarity and consistency in the terminology and methodology of L2 aptitude research.

Another challenge is the lack of generalizability and applicability of L2 aptitude research. Most of the studies on L2 aptitude have been conducted in laboratory settings or in classroom contexts with limited samples of learners and languages (DeKeyser & Koeth, 2011; Granena & Long, 2013). Therefore, it is not clear how well the findings can be generalized to other settings and populations of L2 learners and languages. Moreover, most of the studies on L2 aptitude have focused on describing and explaining the construct rather than applying it to enhance L2 learning and teaching (Dörnyei & Ryan, 2015; Robinson, 2005). Therefore, there is a need for more research on how to use aptitude tests and measures for diagnostic, placement, and instructional purposes (Dörnyei & Ryan, 2015; Robinson et al., 2012).

L2 aptitude research has made significant progress in the last six decades but still faces some challenges and limitations. The future of L2 aptitude research lies in addressing these challenges and limitations by adopting a more dynamic, integrative, and applied approach to the construct. This approach would entail:

Developing a more comprehensive and coherent framework for defining and operationalizing aptitude components and functions that are relevant for different types and stages of L2 learning and processing.
Using a combination of traditional and novel methods and tools to measure aptitude components and functions more directly and objectively and investigate their cognitive mechanisms and neural correlates.
Conducting more studies in naturalistic and diverse settings with larger and more representative samples of learners and languages to increase the generalizability and validity of the findings.
Exploring more ways to use aptitude tests and measures for diagnostic, placement, and instructional purposes to enhance L2 learning outcomes and experiences.

By following this approach, L2 aptitude research can contribute to a better understanding of the cognitive abilities that underlie L2 learning and processing and a better design of L2 instruction that caters to the needs and strengths of individual learners.

Problem-solving 7

Language aptitudes and L2 learning outcomes

You are a teacher of English as a foreign language at a university in China. You have a class of 30 students who are taking an intensive English course for one semester. The course aims to improve their English proficiency in all four skills (listening, speaking, reading, and writing) and prepare them for the IELTS test. The course consists of 20 hours of instruction per week, plus homework and self-study.

At the beginning of the course, you administered the LLAMA Language Aptitude Test to your students to assess their L2 aptitude. You also collected some background information from them, such as their age, gender, motivation, learning style, and previous L2 learning experience. You recorded their scores and information in a spreadsheet.

At the end of the course, you administered the IELTS test to your students to measure their L2 learning outcomes. You also recorded their scores in the same spreadsheet.

You want to analyze the data and answer the following questions:

How do your students’ L2 aptitude scores compare with the average scores reported by the LLAMA website?
How do your students’ IELTS scores compare with the average scores reported by the IELTS website?
How do your students’ L2 aptitude scores correlate with their IELTS scores?
Which components or functions of L2 aptitude are more predictive of L2 learning outcomes in your context?
How do other factors, such as age, gender, motivation, learning style, and previous L2 learning experience, affect L2 learning outcomes in your context?
How can you use the results of your analysis to inform your teaching practice and provide feedback and guidance to your students?

Chapter Summary

In conclusion, foreign language aptitude is a complex construct encompassing various cognitive, affective, and conative factors influencing language learning. The correlational approach to cognition has been widely used to identify the components of aptitude, highlighting the importance of memory capacity, phonetic coding ability, and inductive learning ability, among others. Conation and affect have also been shown to play a significant role in language learning, with motivation, attitudes, and anxiety affecting learners’ success in acquiring an L2.

Aptitude has been found to be a reliable predictor of formal L2 learning rate, with individuals with high aptitude tending to acquire a second language more quickly and efficiently. However, the lack of L2 aptitude or general language-related difficulties can also impact language learning outcomes, and some researchers argue that explicit learning may be less effective than implicit learning, particularly for late-starting learners.

Memory capacity has been identified as a privileged component of L2 aptitude, with working memory and long-term memory playing a crucial role in language acquisition. The contribution of memory to aptitude has been studied extensively, with some researchers suggesting that a combination of working memory, long-term memory, and phonetic coding ability may provide a more accurate measure of language aptitude.

Aptitude and age have also been studied extensively, with researchers suggesting that younger learners may have an advantage in language acquisition due to their greater cognitive flexibility and plasticity. However, recent studies have also shown that older learners can still make significant progress in language learning, particularly when given adequate instruction and support.

Finally, multidimensional aptitudes have emerged as a more recent development in the study of L2 aptitude, taking into account the complex interplay of cognitive, affective, and conative factors in language learning. The future of L2 aptitude research will likely involve more nuanced and multidimensional approaches, incorporating the latest findings from neuroscience and cognitive psychology to further our understanding of how individuals learn languages and how we can optimize language learning outcomes.

Questions to help review the lesson

What is language aptitude?
How is language aptitude related to second language learning?
What is the correlational approach to cognition?
How does conation and affect have effect on language aptitude?
Can aptitude predict the rate of formal L2 learning?
What is the relationship between memory capacity and language aptitude?
What are the contributions of memory to aptitude?
How does age affect language aptitude?
What is multidimensional aptitude?
What are the recent developments in L2 aptitude research?
Can general language-related difficulties be mistaken for lack of L2 aptitude?
How can teachers identify and support students with low L2 aptitude?
What are some strategies that can help students with low L2 aptitude improve their language skills?
What are the ethical implications of using aptitude tests in language learning?
What are some potential future directions for L2 aptitude research?

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