THE THEORETICAL AND PEDAGOGICAL SIGNIFICANCE OF IMPLICIT APTITUDE

The importance of implicit aptitude rests on the assumption that implicit learning exists and that it is separable from explicit learning. According to dual-process theories of human learning, knowledge and skills are acquired in two distinct ways: through explicit learning characterized by effortful and deliberate processing of information and through implicit learning characterized by unconscious computation of the relationships between available materials in the environment. Explicit learning is more recent in human evolution; it is attention-driven, analytic-rational, efficient, short-lived, and transferable between different knowledge and skill domains. It is typically associated with attributes of “being smart” and is measured through traditional intelligence tests. Implicit learning is evolutionarily more primitive in that the initial state of human knowledge is primarily intuitive and tacit knowledge before it becomes conscious and rational. Implicit learning is data-driven, intuitive, slow, sustainable, and not easily transferable between domains. The large body of psychological research conducted in different paradigms, such as artificial grammar, SRT, statistical learning, declarative versus procedural memory, and priming, has provided robust evidence for the existence of implicit learning and its separation from explicit learning. One importance piece of evidence that has been used to prove its existence is that cognitive abilities underlying conscious learning (typically measured using IQ tests) such as associative memory and reasoning are only correlated with the effects of explicit learning tasks but uncorrelated, or even negatively correlated, with the effects of implicit learning tasks (Gebauer & Mackintosh, Reference Gebauer and Mackintosh2007; Reber et al., Reference Reber, Walkenfeld and Hernstadt1991; Robinson, Reference Robinson2005). Evidently, mapping the relationship between implicit and explicit learning abilities and learning outcomes is fruitful in unraveling the relationship between implicit and explicit learning. However, to most psychological researchers, learners differ only in their explicit learning abilities such as IQ, and they do not vary in their ability for implicit learning. Accordingly, most research has investigated the process, outcome, and measurement of implicit learning, instead of conceptualizing it as a cognitive ability. However, there has been evidence that aptitude for implicit learning is “a reliable and stable capacity of the individual” (Siegelman & Frost, Reference Siegelman and Frost2015, p. 18) because of its high test-retest reliability and its predictive power for outcome variables (Siegelman et al., Reference Siegelman, Bogaerts and Frost2017). Therefore, there is a need to add implicit aptitude in the theory and research on the implicit-explicit distinction.

In SLA, the focus of theory and research has been on the debate over whether second language learning is explicit or implicit (Krashen, Reference Krashen and Diller1981), the comparative effectiveness of explicit and implicit instruction (Kang et al., Reference Kang, Sok and Han2019; Norris & Ortega, Reference Norris and Ortega2000), and the measurement of explicit and implicit knowledge (R. Ellis, Reference Ellis2005). The explicit versus implicit distinction was not made in aptitude research until recently. The research on language aptitude has centered on explicit aptitude (phonetic coding, analytic ability, and rote memory), and there has been little theorization and research on implicit aptitude. Here, we would like to contextualize the discussion of implicit aptitude by examining its role in major SLA theories because the theoretical claims have important implications for how to conceptualize and operationalize this new construct. It is worth clarifying that these theories do not make explicit claims about the role of language aptitude, but their claims about how learning occurs are suggestive of the mediating role of implicit and explicit aptitude.

First, according to the usage-based approaches to SLA, “the bulk of language acquisition is implicit learning from usage” (N. Ellis, Reference Ellis2005, p. 306); language learning is input-based and relies primarily on the implicit tallying of available cues regarding the relationship between units of the linguistic materials learners encounter. The theory also holds that language learning is a matter of sequence learning: sequences of sounds, words, and phrases and the regularities underlying the sequences. The claims about how learning occurs based on usage-based approaches coincide with the mechanism of implicit aptitude, which has been operationalized as sequence learning, tested through SRT tasks where subjects learn the probabilistic relationships between stimuli through repeated exposure without awareness. Ellis further argues that explicit learning is also necessary, but its role is restricted to certain aspects of vocabulary and to focusing learners’ attention on nonsalient structures that may go unnoticed by learners. However, even in cases in which explicit learning happens, its purpose is to help learners establish initial representations of the constructions and prepare learners for implicit learning.

The usage-based approaches have a profound influence on the claims about the role of implicit learning in the Interaction Hypothesis, a currently popular SLA theory proposed by Long (Reference Long, Ritchie and Bhatia1996, Reference Long2015). The core tenet of the Interaction Hypothesis is that the optimal condition for L2 learning is when learners’ attention is drawn to linguistic forms during meaning-primary interaction. Attention to form needs to be brief, reactive, and ideally provided through implicit negative feedback such as recasts, which refer to the reformulation of an erroneous utterance without changing the meaning. In what way is this theory related to implicit aptitude? Similar to the usage-based approaches, the Interaction Hypothesis holds that implicit learning is the default learning mechanism of second language acquisition. However, according to Long (Reference Long2015), the ability for implicit learning, which children have full access to, declines in adults. Therefore, implicit learning by adults needs to be aided by “intentional initial perceptions of new forms and form-meaning connections” (p. 49). Long further argued that the initial perception requires minimal attentional resources and does not require metalinguistic awareness of forms. The purpose of this level of attention is to “tune in to” selected input, and further processing of the input will be taken over by implicit learning after the initial representation. Long also cited evidence that implicit and explicit learning are conducive for the learning of different structures: while the former advantages adjacent items (e.g., AB) and complex structures, the latter favors structures involving long-distance dependencies (AXB) and simple structures. However, there is evidence that implicit learning is effective for both adjacent and nonadjacent structures (Misyak & Christiansen, Reference Misyak and Christiansen2012). Overall, it can be inferred that implicit aptitude plays a key role in the Interaction Hypothesis and that implicit aptitude is at its best when aided by low levels of attention—perception or detection, not understanding or metalinguistic awareness.

Skill Acquisition Theory (DeKeyser, Reference DeKeyser, VanPatten, Keating and Wulff2020) posits three stages involved in language learning: declarative knowledge, proceduralization, and automatization. Declarative knowledge refers to knowledge about language such as grammar rules, word-meaning associations, and knowledge about sounds. Declarative knowledge is proceduralized when applied in actual linguistic behaviors and is automatized through repeated practice. DeKeyser indicated that the declarative-procedural distinction is largely equivalent to the explicit-implicit distinction, although they are not entirely identical. As to the role of language aptitude, DeKeyser stated that Skill Acquisition Theory attaches importance to language aptitude “because of its emphasis on the importance of explicit/declarative knowledge in initial stages of learning” (Reference DeKeyser, VanPatten, Keating and Wulff2020, p. 91). Clearly, language aptitude refers to traditional explicit aptitude in this claim. Given that proceduralization and automatization involve implicit learning, implicit aptitude is likely implicated at these two stages of learning, which are more advanced than declarative knowledge. A corollary is that explicit aptitude is involved more in initial learning and implicit aptitude more in advanced learning. DeKeyser pointed out that in addition to playing different roles at different learning stages, there are other ways implicit and explicit learning work in “synergy.” For example, implicit learning may lead to implicit knowledge, and explicitly learned knowledge may lead to automatized knowledge that is functionally equivalent to implicit knowledge. Based on this argument, it can be hypothesized that both implicit and explicit aptitude contribute to implicit knowledge in that the former plays a direct role in leading to implicit knowledge and the latter plays an indirect role by means of facilitating automatized L2 knowledge that may not be discernable from implicit knowledge. However, as DeKeyser pointed out, the primary concern of Skill Acquisition Theory is how declarative knowledge can be effectively learned and how it is proceduralized and automatized through practice, and whether the eventual knowledge is implicit or explicit is of less importance.

Another theory that makes similar but not identical claims as Skill Acquisition Theory is the Declarative/Procedural (D/P) Model. Similar to Skill Acquisition Theory, the D/P model makes a distinction between declarative and procedural systems, but instead of treating them as knowledge, in the D/P model they are referred to as two types of long-term memory where knowledge is learned and stored. In this model, declarative memory is responsible for the learning of “idiosyncratic (non-derivable) information and arbitrary associations” (Ullman & Lovelett, Reference Ullman and Lovelett2018, p. 41), including words (spelling, meaning, sound-meaning associations), idioms, and unanalyzed chunks (including irregular morphological forms such as irregular verb past forms). Procedural memory, which is “a type of implicit memory system” (Buffington & Morgan-Short, Reference Buffington, Morgan-Short, Wen, Skehan, Biedron, Li and Sparks2019, p. 217), is responsible for grammar learning or the learning of sequences, rules, and patterns. However, Ullman claims that grammar can also be learned in declarative memory, which is especially true of adults whose procedural memory is not as strong as their declarative memory. Declarative memory holds primarily explicit knowledge, but it also stores implicit knowledge; however, all explicit knowledge is learned in declarative memory. Procedural memory is the only storage space for implicit knowledge, although there are different mechanisms for learning implicit knowledge (such as priming, sequence learning, etc.). The learning that happens in declarative memory is fast and requires minimal exposure, while in procedural memory learning is slow and gradual and requires massive exposure. Whether learners deploy their procedural or declarative memory depends on external factors such as the learning setting, for example, explicit instruction will encourage learners to utilize their declarative memory and, in the absence of explicit instruction, learners will have to rely on their procedural memory. One important claim of the D/P model is that the activation of one memory system may inhibit or override the other. Based on the claims of the D/P model, we can roughly equate declarative memory with explicit aptitude and procedural memory with implicit aptitude, although the scope of aptitude is larger than memory. For example, declarative memory has been operationalized as rote (associative) memory and recognition memory, while in the paradigm of language aptitude explicit aptitude encompasses phonetic coding and analytic ability in addition to rote memory. In cognitive psychology, declarative and procedural memory are called explicit and implicit memory, respectively (Goldstein, Reference Goldstein2011). Finally, the D/P model focuses more on the different functions and contents of the two types of long-term memory than on how declarative memory can be proceduralized through practice—a main concern of Skill Acquisition Theory.

To conclude the theoretical discussion of the role of implicit aptitude (and in relation to explicit aptitude),² we would like to summarize the main claims derived from the above-mentioned SLA theories. Although most of these claims are theoretical and have yet to be tested in aptitude research, they provide insights that may serve as hypotheses to be examined empirically.

• • Implicit aptitude makes an independent contribution to SLA by means of unconsciously extrapolating the regularities governing the distribution and contingencies of linguistic input.

• • Implicit aptitude contributes to the learning of structures involving adjacent items as well as structures involving long-distance dependencies.

• • Implicit aptitude is more effective for complex structures while explicit aptitude may have larger effects for simple structures.

• • Implicit aptitude is more efficient when learners process input initially established in their focal attention but the amount of attentional resources required for such initial representation is minimal—unlike the high levels of awareness and participatory demands required for explicit learning.

• • Implicit aptitude is more likely to be implicated in advanced L2 learning while explicit aptitude is more important in initial learning.

• • Implicit aptitude may contribute directly to implicit knowledge while explicit aptitude may contribute to implicit knowledge indirectly by providing fodder (declarative knowledge) for implicit learning.

• • Implicit aptitude is slow and requires repeated exposure while explicit aptitude is quick and efficient.

• • Implicit aptitude is more likely to be resorted to when there is a lack of external force diverting learners’ attention to linguistic forms while explicit aptitude is drawn on when learners are required or encouraged to consciously process linguistic materials.

• • Other things being equal, implicit aptitude is more likely to be implicated in grammar learning while explicit aptitude plays a greater role in lexical learning.

• • Implicit and explicit aptitude may interfere with each other in certain learning conditions.

Research on implicit aptitude may not only enhance our understanding of the theory and mechanisms of SLA but also provide valuable pedagogical implications. First, results of aptitude tests have been used to select candidates with the potential to master a foreign language within a short period (such as in state-funded language programs in the United States), place learners with comparable aptitude levels into different streams of classes, provide counseling to learners in terms of adopting strategies that fit their aptitude profiles, make decisions about waiving foreign language requirements, and evaluate the effectiveness of instruction (Li, Reference Li, Loewen and Sato2017b, Reference Li, Burns and Richards2018, in press). However, current aptitude assessment is dominated by tests of explicit aptitude such as the MLAT (Carroll & Sapon, Reference Carroll and Sapon2002) and other tests modeled on the MLAT such as the LLAMA (Meara, Reference Meara2005). If implicit aptitude makes an independent contribution to L2 attainment, then the assessment of language aptitude should include measures of implicit aptitude, and an aptitude test without implicit aptitude is incomplete. Second, the notion of implicit aptitude fits the mechanism of the currently popular task-based instruction and other meaning-oriented approaches where language is taught through meaning-primary tasks (Ellis et al., Reference Ellis, Skehan, Li, Shintani and Lambert2020; Long, Reference Long2015). These approaches seek to foster learners’ communicative competence, which draws primarily on implicit knowledge. It can be hypothesized that implicit aptitude will be more likely to be involved in meaning-oriented instruction and explicit aptitude is more strongly correlated with the effects of more form-oriented instruction. If the hypothesis is confirmed, the findings will provide evidence that (a) learning happens through two different processes under different learning conditions, (b) different instructional approaches work for learners with different aptitude profiles, and (c) learners who are classified as not having the intelligence or prowess for language learning based on traditional aptitude measures may be stronger in unconscious learning and therefore have better chances of success if they are taught in ways that unlock their strengths.

THE NATURE, COMPONENTS, AND OPERATIONALIZATION OF IMPLICIT APTITUDE

In this section, we attempt to identify the nature of implicit language aptitude based on the literature on implicit learning and language aptitude. We then discuss the possible components the construct comprises and tests or tasks that have been or can be used to measure the components.

IMPLICIT APTITUDE AND SECOND LANGUAGE ACQUISITION

To date, there has been limited research on implicit aptitude’s associations with L2 learning. The limited research can be roughly divided into two categories based on the research setting: naturalistic and instructed. In a naturalistic setting, the target language is also the language of the community, and learners have opportunities for exposure to the L2 in their everyday life. An instructed setting is one where L2 learning happens primarily in the classroom, whether virtual or physical. The studies conducted in naturalistic settings can be subdivided into two groups. One group investigated the associations between aptitude and the ultimate attainment of learners who arrived in the country of the L2 at different ages. These studies were conducted with learners who had lived in the country of the L2 for at least 8 years. Granena (Reference Granena2013) investigated whether implicit aptitude measured by SRT and LLAMA_D was correlated with the ultimate attainment of early and late bilinguals. It was found that SRT was predictive of late bilinguals’ implicit knowledge measured through a word-monitoring task, while LLAMA_D was predictive of early bilinguals’ explicit knowledge assessed using a grammaticality judgment test (GJT). Other age-related studies that only included explicit aptitude shed further light on the interface between age and aptitude. DeKeyser’s (Reference DeKeyser2000) seminal study showed that explicit aptitude measured by the Words in Sentences subtest of the HUNLAT (a measure of language analytic ability) was predictive of late, but not early, bilinguals’ scores on an aural GJT. Abrahamsson and Hyltenstam (Reference Abrahamsson and Hyltenstam2008) only investigated L2 learners who passed for native speakers. They reported that (a) late bilinguals all had high aptitude (measured using an early version of LLAMA) while early bilinguals and native speakers showed varied levels of aptitude; and (b) aptitude showed a significant correlation with early bilinguals’ scores on a challenging GJT (r = .70, p < .01) and a near-significant correlation with late bilinguals’ GJT scores (r = .57, p = .09). Granena and Long (Reference Granena and Long2013) explored aptitude’s associations with Chinese speakers’ L2 Spanish proficiency. They found that total LLAMA scores, which mainly represent explicit aptitude, correlated with late bilinguals’ (age of onset > 16) vocabulary and pronunciation, but not early bilinguals’ (age of onset: 3–6) Spanish proficiency. These studies suggest that explicit aptitude is more likely to be involved in late bilinguals’ L2 attainment and implicit aptitude is drawn upon by both early and late bilinguals. However, the conclusion is not unequivocal because of the disparate findings of the research.

The other group of naturalistic studies investigated the predictive power of implicit aptitude for the L2 proficiency of learners who arrived in the country of the L2 during adulthood. These studies involved learners who had lived in the country of the second language for less than 3 years (Saito et al., Reference Saito, Sun and Tierney2019; Suzuki & DeKeyser, Reference Suzuki and DeKeyser2015, Reference Suzuki and DeKeyser2017; Yi, Reference Yi2018). One commonality between the studies is that they all examined L1 Chinese speakers, and the homogeneity of the learners’ L1 background, albeit coincidental, may increase the robustness of the findings. These studies afford further insights into aptitude-learning associations in naturalistic settings. Saito et al. (Reference Saito, Sun and Tierney2019) explored whether Chinese speakers’ implicit and explicit phonetic aptitude was associated with their L2 English speech performance. They used an electrophysiological method to measure implicit aptitude and LLAMA_E and a test of music aptitude (abilities to discriminate melody and rhythm) to measure explicit aptitude. They reported significant effects for both types of aptitude on L2 pronunciation learning. Saito et al.’s study is seminal in that it is among the first to investigate implicit and explicit pronunciation aptitude in L2 speech performance. The study also proposed a framework mapping the relationships between implicit and explicit pronunciation aptitude and segmental (sounds) and suprasegmental (word stress, rhythm, etc.) accuracy. The two studies by Suzuki and DeKeyser examined L1 Chinese speakers’ L2 Japanese proficiency, and the primary objective of the studies was to explore the relationship between implicit and explicit knowledge by drawing on the concept of implicit and explicit aptitude. Taken together, the two studies revealed that (a) implicit aptitude measured by SRT was positively correlated with long-residence learners’, but not short-residence learners’, implicit knowledge of L2 Japanese morphosyntax measured using a word monitoring test; (b) SRT was negatively, albeit nonsignificantly, correlated with short-residence learners’ implicit knowledge; and (c) explicit aptitude measured by LLAMA_F was predictive of explicit knowledge (automatized). Yi (Reference Yi2018) demonstrated that in a U.S. context, L1 Chinese L2 English speakers’ knowledge about English collocations was significantly correlated with their explicit aptitude (LLAMA_B/_E/_F) but not their implicit aptitude (SRT).

What do we make of the results of these naturalistic studies? As can be seen, the results are quite mixed, but overall the following patterns can be extracted. First, implicit aptitude is predictive of naturalistic L2 learning, but its effects seem more likely to be evident in learners who have resided in the country for longer periods (Granena, Reference Granena2013; Suzuki & DeKeyser, Reference Suzuki and DeKeyser2017). Second, explicit aptitude is predictive of late, but not early, bilinguals’ L2 attainment (Granena & Long, Reference Granena and Long2013; Suzuki & DeKeyser, Reference Suzuki and DeKeyser2015; Yi, Reference Yi2018), but there are exceptions (Abrahamsson & Hyltenstam, Reference Abrahamsson and Hyltenstam2008). Third, the relationship between implicit and explicit knowledge and implicit and explicit aptitude is unclear.

Next, we proceed to the studies on instructed learning. We further divide these studies into two categories: correlational and experimental. In correlational research, there is no instructional treatment, and the interest is in whether aptitude is correlated with L2 proficiency. (In this sense, all the naturalistic studies are correlational.) In experimental research, learners receive instructional treatments, and the objective is to show whether aptitude is drawn on differently under different learning conditions. Starting with correlational research, Granena’s (Reference Granena2019) study involved learners of Spanish whose native language is English at a large U.S. university. The researcher administered the Hi-LAB aptitude battery and the LLAMA tests and explored the relationship between explicit and implicit aptitude and L2 speech performance coded as complexity, accuracy, and fluency. The study showed no effects for explicit aptitude (LLAMA_B/_E/_F + MLAT_5 + Letter Recall) and a significant effect for implicit memory (semantic priming + LLAMA_D) on fluency. An interaction between implicit memory and SRT—a measure of implicit aptitude—was found such that implicit memory was important for lexical complexity only among learners with high SRT scores. Link et al.’s (2013) seminal study attempted to identify cognitive abilities for high-level proficiency operationalized as L2 Spanish speakers’ listening and reading scores on a proficiency test and their high-level job performance in the L2. The researchers reported that among the 13 measures of cognitive ability, implicit aptitude (SRT), phonological short-term memory, and rote memory were significant predictors. Saito et al.’s (Reference Saito, Sun and Tierney2019) study, conducted with Japanese learners of English in Tokyo, reported that explicit aptitude (LLAMA_B and _E) was predictive of learners’ speech fluency during their first semester’s study, whereas implicit aptitude (LLAMA_D) showed an important effect on their pronunciation development in the second semester.

In the experimental research, the studies by Yilmaz and Granena (Granena & Yilmaz, Reference Granena and Yilmaz2019; Yilmaz & Granena, Reference Granena2019) investigated whether explicit and implicit aptitude fared differently when L1 English L2 Spanish learners at a large U.S. university received explicit and implicit feedback. They found that implicit aptitude (SRT) was correlated with the effects of implicit feedback, and explicit aptitude operationalized as phonological short-term memory was predictive of the effects of explicit feedback. The significant results for implicit aptitude were only obtained for the gender agreement, not the other target structure—object case marking. The studies by Hamrick (Reference Hamrick2015) and Morgan-Short et al. (Reference Morgan-Short, Faretta-Stutenberg, Brill-Schuetz, Carpenter and Wong2014) were conducted within the framework of the Declarative/Procedural model. In Morgan-Short et al.’s study, native speakers of English learned an artificial language in an incidental condition—they were never taught grammar rules, and they learned the language by engaging in meaning-oriented comprehension and production activities. They took two tests of procedural memory (implicit aptitude) (Tower of London and Weather Prediction) and two tests of declarative memory (explicit aptitude) (MLAT_5 and CVMT). Treatment effects were measured twice using a GJT: after the first two treatment sessions and after all four treatment sessions. It was found that declarative memory was predictive of the first posttest scores and procedural memory was correlated with the second posttest scores. Hamrick (Reference Hamrick2015) also examined the role of procedural and declarative memory in incidental learning, but the memory tests (SRT and LLAMA_B, respectively) and learning task (three Persian structures built into English sentences) were different from those in Morgan-Short et al.’s study. Significant effects were found for declarative memory on the learners’ posttest scores immediately after the treatment, and for procedural memory on their scores on a delayed posttest (administered 2 weeks after the treatment). Both Morgan-Short et al. and Hamrick claimed that their studies showed that declarative memory is relevant at initial stages of L2 learning and procedural memory at later stages.

To summarize the research on instructed learning, we can observe the following patterns. First, the correlational studies showed that implicit aptitude is predictive of foreign language learners’ speech performance (Granena, Reference Granena2019; Saito et al., Reference Saito, Sun and Tierney2019) and high-level proficiency in listening and reading comprehension (Linck, Reference Linck, Hughes, Campbell, Silbert, Tare, Jackson, Smith, Bunting and Doughty2013), suggesting implicit aptitude’s links with implicit knowledge, which is probably represented in both outcome measures. Second, the experimental studies showed that under highly controlled incidental learning conditions, learners are more likely to draw on explicit aptitude initially and implicit aptitude at later stages (Hamrick, Reference Hamrick2015; Morgan-Short et al., Reference Morgan-Short, Faretta-Stutenberg, Brill-Schuetz, Carpenter and Wong2014). In this case, the learners were exposed to artificial languages and had zero knowledge about the target languages. The studies conducted with learners with some previous knowledge about the target language (Spanish) demonstrate that learners draw on implicit aptitude when receiving implicit instruction and explicit aptitude when receiving explicit instruction (Granena & Yilmaz, Reference Granena and Yilmaz2019; Yilmaz & Granena, Reference Granena2019). However, due to limited research, the results need to be interpreted with reference to the idiosyncratic methodological features of these studies. For example, in the case of the studies by Granena and Yilmaz, the results may have changed if an analytic measure of explicit aptitude was used and/or if the explicit feedback was operationalized as metalinguistic feedback rather than explicit correction. Also, the research examined a narrow range of target structures, and there may exist an interaction between aptitude type and the target structure (DeKeyser, Reference DeKeyser2012; Li, Reference Li and Han2014). Therefore, at this point, no firm conclusions can be reached, and further research is needed before a clear picture can be provided. The lack of clear and consistent findings in this research area so far is an incentive for this special issue.

THE SPECIAL ISSUE

To date, the research on cognitive abilities for second language learning has been dominated by explicit aptitude, which requires effortful and conscious encoding, processing, storage, and retrieval of linguistic input. There has been little theorization and research on implicit aptitude. The study of implicit aptitude is challenging because of the elusive and uncontrolled nature of implicit learning and the resultant difficulty in designing tasks to capture its effects and gauge the underlying ability. This special issue takes the challenge by contributing seven empirical studies examining implicit aptitude from various perspectives with a view to drawing attention to this newly emerged construct, exemplifying ways to examine the construct, and deepening our understanding of its nature and mechanism. In the following, we provide an overview of the seven included studies and discuss in what way they contribute to the study of implicit aptitude.

Buffington, Demos, and Morgan-Short examined the convergent and divergent validity of tasks/tests of procedural memory, which we equate with implicit aptitude. Convergent validity refers to whether the tasks purported to measure the same construct—procedural memory in this case—are correlated with each other, and divergent validity refers to whether the tasks of procedural memory are uncorrelated or less strongly correlated with measures of declarative memory, which is theoretically distinct from procedural memory. Ninety-nine undergraduate students at a large U.S. university completed three tasks for procedural memory and three for declarative memory. Procedural memory was tested through SRT, weather prediction, and Tower of London. Declarative memory was measured using a test of rote memory (MLAT_5) and two memory recognition tasks: Continuous Visual Memory Test (CVMT) and Declearn. The results showed that (a) CVMT, Declearn, and weather prediction loaded onto the same factor, (b) SRT loaded onto another factor, and (c) the other measures did not have acceptable factor loadings in any factor. These results were unexpected in that weather prediction was intended to be a measure of procedural memory but loaded onto the factor of declarative memory and that the three measures of procedural memory were uncorrelated with each other. The results suggested a lack of convergent validity of the procedural memory tasks, and a lack of divergent validity of the weather prediction task. Based on the results, the researchers suggested not using weather prediction as a measure of procedural memory and having a clear notion of what kind of ability is intended to be tapped when using a particular test in future research.

Fu and Li’s contribution is an ATI (aptitude-treatment-interaction) study investigating the complicated relationship between types of aptitude and types of treatment. It examined whether implicit aptitude operationalized as procedural memory and explicit aptitude as declarative memory and working memory have differential associations with the effectiveness of immediate and delayed corrective feedback. The subjects were 112 seventh-grade EFL learners, who were divided into three groups and received immediate, delayed, or no feedback, depending on their group assignment. Immediate feedback was provided during a communicative task immediately after the learners received grammar instruction about the target structure (the English past tense), and delayed feedback was provided 2 weeks after the initial grammar instruction and after the learners completed some communicative practice. Treatment effects were tested using a GJT (explicit knowledge) and an elicited imitation test (implicit knowledge). Procedural memory was measured through a SRT task, declarative memory was tested by means of a memory recognition task, and working memory was gauged using an operation span task. It was found that procedural memory was predictive of the effects of immediate feedback, declarative memory was associated with the effects of delayed feedback, and working memory was involved in both immediate and delayed feedback. The significant effects were evident only on the elicited imitation test, not the GJT. The results suggested that the three types of memory have differential relationships with different instructional treatments. Fu and Li argued that the role of procedural memory was evident in immediate feedback probably because (a) learners had sufficient declarative knowledge that resulted from the grammar instruction and was solidified through immediate feedback, and (b) immediate feedback may have expedited the proceduralization of declarative knowledge by drawing learners’ attention to the target structure. Declarative memory was predictive of the effects of delayed feedback because the feedback prompted learners to draw on their declarative memory to retrieve the declarative knowledge obtained through the grammar instruction provided two weeks ago and to learn new declarative knowledge from feedback. Working memory was implicated in both feedback conditions because of the heavy processing load imposed on learners by online feedback provided during task performance (Li et al., Reference Li, Ellis and Zhu2019). Finally, the mapping between implicit and explicit aptitude and implicit and explicit knowledge was unclear, similar to what transpired in Yilmaz and Granena’s study (see following text).

Godfroid and Kim’s study aimed to map the relationship between implicit aptitude and implicit and explicit knowledge. One hundred and thirty-one ESL learners at a large U.S. university whose average length of residence in the country was 41 months took two tests of implicit knowledge: word monitoring and self-paced reading; four tests of automatized explicit knowledge: timed aural grammaticality judgement (GJT), timed written GJT, elicited imitation, and oral production; and three tests of explicit knowledge: untimed aural GJT, untimed written GJT, and metalinguistic knowledge. They also took four tests of implicit aptitude: sequence learning (SRT), auditory statistical learning, visual statistical learning, and Tower of London. The results showed poor convergent validity of the measures of implicit aptitude—they were largely uncorrelated—except for a strong correlation between the two measures of statistical learning. The researchers also examined the measurement model for the proficiency measures, testing a two-factor model (implicit knowledge and explicit knowledge) and a three-factor model (implicit knowledge, explicit knowledge, and automatized explicit knowledge). They found better fit indices for the two-factor model and therefore elected to follow that model in further analyses. In a subsequent structural equation modeling analysis, a significant, positive path was detected between sequence learning and implicit knowledge, and no other paths were significant. The findings showed a lack of correlations between different measures of implicit aptitude and the robustness of sequence learning as a predictor of L2 attainment compared with other measures of implicit aptitude.

Li and Qian explored syntactic priming as a measure of implicit aptitude. The study is motivated by the semantic vacuity of existing measures and the fit of the mechanism of syntactic priming with the mechanism of language learning. One hundred sixty-six L2 English learners at a Chinese university were given three tests of implicit aptitude: priming, SRT, and LLAMA_D; three tests of explicit aptitude: LLAMA_B, _E, and _F; two tests of explicit knowledge: GJT and metalinguistic knowledge; and one test of implicit knowledge: elicited imitation. The three measures of implicit aptitude failed to show convergent validity. LLAMA_D loaded onto the factor of explicit aptitude, and syntactic priming was negatively correlated with sequence learning. Structural equation modeling analyses mapping the relationships between aptitude and proficiency measures showed that syntactic priming was a negative predictor of metalinguistic knowledge, sequence learning was not a significant predictor of any proficiency measure, and explicit aptitude was a strong predictor of L2 proficiency. The proficiency factor comprised all three outcome measures including elicitation imitation, which was hypothesized to measure implicit knowledge. The findings provided further evidence for the multidimensional and multicomponential nature of implicit aptitude. The researchers interpreted the findings by comparing the different mechanisms of sequence learning and priming, highlighting the need for further research into the validity of priming as a measure of implicit aptitude. The researchers also discussed the challenge in assessing the implicit knowledge of learners in a foreign language setting where the instruction is heavily form oriented, which may lead to knowledge that is primarily explicit. This explanation sheds light on the disparity between the findings of Li and Qian’s study and Godfroid and Kim’s study where implicit and explicit knowledge were separable and a positive link was found between sequence learning and automatized explicit L2 knowledge. Although the designs of the two studies are similar, Li and Qian’s study was conducted in a foreign language setting while Godfroid and Kim’s study involved learners in a naturalistic setting where implicit or automatized explicit knowledge is more likely to develop. Although the validity of syntactic priming as a measure of implicit aptitude was not established, the study contributes insights into the methods of aptitude research and the potential for further research on the topic.

Sun, Saito, and Tierney investigated the associations between implicit and explicit auditory processing abilities and L2 speech perception in a naturalistic setting. The subjects were 46 L1 Chinese L2 English learners in London who had lived in the country for around five months. Explicit auditory processing was measured by means of two auditory processing tests: sound discrimination threshold and music memory, and implicit auditory processing was gauged through a test of neural encoding of sound. The sound discrimination threshold test asked learners to distinguish sounds varying in pitch, formant, duration, and amplitude rise time. In the test of music memory, learners were required to repeat a melody or rhythm to which they listened. In the test of implicit auditory processing, learners listened to a /da/ sound for 20 minutes while reading a book or magazine. Electrodes were placed on their heads to record their electrophysiological responses, which then served as a proxy of their neural encoding of sound. Speech perception, the outcome variable, was measured through a minimal pair sound recognition test at two time points with an interval of five months. The learners made significant improvements only in prosody perception but not in vowel perception, which was not further analyzed. The results demonstrated that music memory was the only significant predictor of prosody perception. The researchers interpreted the findings as suggesting that explicit aptitude is important at an initial stage of immersion, that the learners’ length of residence is not long enough for the effect of implicit aptitude to be evident, and that implicit aptitude may be important for the segmental (not analyzed because of ceiling effects) but not suprasegmental (prosody) perception. This study represents an attempt to investigate the domain-specific nature of implicit aptitude in that it examined the associations between pronunciation aptitude and pronunciation learning. It also exemplifies how implicit aptitude can be gauged through a neurological measure—an innovation in aptitude research. The finding confirms the findings of existing naturalistic studies that short-residence learners draw on explicit aptitude (Yi, Reference Yi2018) and that implicit aptitude only plays a role in the L2 gains of long-residence learners (Granena, Reference Granena2013; Suzuki & DeKeyser, Reference Suzuki and DeKeyser2015). However, the study did not include a measure of implicit knowledge, which could have correlated with implicit aptitude.

Suzuki’s study seeks to improve the validity of LLAMA_D as a measure of implicit aptitude. Fifty-nine L1 Japanese university students took LLAMA_D and the other three subtests (LLAMA_B, _E, and _F) that were purported to measure explicit aptitude, and they also completed an oral production task in L2 English. During the LLAMA_D, the participants were asked to listen to 20 disyllabic sounds, followed by a testing phase where they listened to the old sounds as well as 10 new sounds and decided whether each was old or new. To encourage incidental learning, the instructions for LLAMA_D were modified, requiring the learners to check the sound volume while listening to the sound stimuli and not informing them of the subsequent test phase. The learners were asked to rate their confidence levels for their responses when asked to recognize whether an item was an old or new item in the testing phase. The study found that LLAMA_D was separate from the other LLAMA subtests; the participants’ responses to old and new items represented separate processes; the participants’ confidence ratings were related to the accuracy and reaction time of their responses, suggesting that they were conscious of what they learned; and the CV (coefficient of variance) of the reaction time measure of LLAMA_D was significantly predictive of the mid-clause fluency of the learners’ L2 speech performance—a measure of implicit knowledge. Based on the results, the researcher recommended separating the old and new items of LLAMA_D, using the instructions that encouraged incidental learning, and calculating the CV of reaction time in future research.

Yilmaz and Granena conducted a complicated ATI study examining the double-dissociation hypothesis, that is, implicit aptitude will correlate with the effects of implicit instruction but not the effects of explicit instruction, and explicit aptitude will correlate with the effects of explicit instruction but not the effects of implicit instruction. One hundred thirteen L2 Spanish learners at a U.S. university were divided into three groups—explicit feedback operationalized as explicit correction, implicit feedback that took the form of recasts, and control, who only performed treatment tasks without receiving any feedback. The target structures were Spanish noun-adjective gender agreement and differential object marking (DOM). The aptitude measures included the LLAMA aptitude battery and several subtests of the Hi-LAB (Linck, 2013) including phonological short-term memory (PSTM), sequence learning (SRT), semantic priming, and rote memory. The learners completed two information gap tasks in dyadic interaction with the researcher, during which the experimental groups received corrective feedback on their wrong production of the target structures. Treatment effects were measured by means of a GJT, which was intended to be a test of explicit knowledge, and an oral production test, a measure of implicit knowledge. An exploratory factor analysis of the data for the aptitude measures yielded three factors: implicit learning (SRT + PSTM), implicit memory (LLAMA_D + semantic priming), and explicit aptitude (LLAMA_B + LLAMA_E + LLAMA_F + rote memory). It was found that implicit aptitude in the form of implicit learning was predictive of the effects of implicit feedback on the GJT test in the learning of gender agreement and that explicit aptitude was associated with the effects of explicit feedback in the learning of DOM. The study provides preliminary evidence for the double-dissociation hypothesis. One contribution of the study is the finding that implicit aptitude may potentially be divided into implicit learning ability and implicit memory ability. Another thought-provoking finding is the possible interface between aptitude type and the target structure. Specifically, implicit aptitude in the form of sequence learning was important for gender agreement—a structure that involves agreement between adjacent items and opaque form-meaning mapping. Explicit aptitude, however, was important for DOM, which involves transparent form-meaning mapping (only animacy was manipulated for this structure). Finally, implicit aptitude had a negative correlation with the effects of explicit feedback while explicit aptitude had a negative correlation with the effects of implicit feedback, although both correlations were nonsignificant. This finding constitutes further evidence for the double-dissociation hypothesis.