linguistic relativity in sla: toward a new research program

Language Learning ISSN 0023-8333

CONCEPTUAL REVIEW ARTICLE

Linguistic Relativity in SLA: Toward a New

Research Program

Emanuel Bylunda and Panos Athanasopoulosb

aStockholm University and Stellenbosch University and bLancaster University

The purpose of the current article is to support the investigation of linguistic relativityin second language acquisition and sketch methodological and theoretical prerequisitestoward developing the domain into a full research program. We identify and discussthree theoretical-methodological components that we believe are needed to succeed inthis enterprise. First, we highlight the importance of using nonverbal methods to studylinguistic relativity effects in second language (L2) speakers. The use of nonverbaltasks is necessary in order to avoid the circularity that arises when inferences aboutnonverbal behavior are made on the basis of verbal evidence alone. Second, we identifyand delineate the likely cognitive mechanisms underpinning cognitive restructuring inL2 speakers by introducing the theoretical framework of associative learning. By doingso, we demonstrate that the extent and nature of cognitive restructuring in L2 speakers isessentially a function of variation in individual learners’ trajectories. Third, we offer anin-depth discussion of the factors (e.g., L2 proficiency and L2 use) that characterize thosetrajectories, anchoring them to the framework of associative learning, and reinterpretingtheir relative strength in predicting L2 speaker cognition.

Keywords linguistic relativity; second language learning; associative learning; Whorf;thinking for speaking

Introduction

The question of whether the language we speak shapes the way we think aboutreality has been a central topic in a number of research disciplines, rangingfrom linguistics and philosophy to anthropology and psychology. The linguist

We wish to thank Lourdes Ortega and the anonymous Language Learning reviewers for their

valuable feedback on this article. This project was funded by the Swedish Research Council (Grant

No. 421-2010-2104).

Correspondence concerning this article should be addressed to Emanuel Bylund, Stockholm Uni-

versity, Centre for Research on Bilingualism, Universitetsvagen 10D, Stockholm 10691 Sweden.

E-mail: [email protected]

Language Learning 64:4, December 2014, pp. 952–985 952C© 2014 Language Learning Research Club, University of MichiganDOI: 10.1111/lang.12080

Bylund and Athanasopoulos Linguistic Relativity in SLA

Benjamin Lee Whorf captured this problem in his principle of linguistic rela-tivity, according to which speakers of different languages are pointed by theirgrammars to different acts of evaluation of reality and therefore must arrive atsomewhat different worldviews (Whorf, 1941/1956, p. 221). The basic tenet ofthe linguistic relativity principle is thus that crosslinguistic differences in thesemantic partitioning of reality (language diversity) give rise to crosslinguis-tic differences in cognition (Levinson, 2012). Whereas empirical research intolinguistic relativity was scarce up until the 1990s, the past two decades havebeen characterized by a remarkable surge in experimental studies on the effectsof language on cognition. By directly operationalizing linguistic influences oncognitive processes using behavioral (e.g., Davidoff, Davies, & Roberson, 1999;Dolscheid, Shayan, Majid, & Casasanto, 2013; Lucy, 1992b) and, more recently,neurophysiological techniques (Thierry, Athanasopoulos, Wiggett, Dering, &Kuipers, 2009), modern studies have explored the linguistic relativity prin-ciple in a number of perceptual domains, such as color, number, time, andspace (for recent reviews, see Casasanto, 2008; Gleitman & Papafragou, 2013;Regier & Kay, 2009; Wolff & Holmes, 2011). Many of these studies suggestthat, while language does not determine our thoughts (which was never sug-gested by Whorf), and while thinking is very much possible without the aid oflanguage (also recognized by Whorf), language nonetheless provides a readybasis of information for the purposes of habitually classifying the world intomeaningful categories (Lucy, 1997). A steadily growing body of experimentalevidence shows that the extent to which humans utilize the linguistic categoriesat their disposal when asked to make judgments about perceptual phenomenadepends on a number of factors, such as the specific characteristics of the per-ceptual domain involved, the nature of the particular linguistic feature underinvestigation, and the degree to which the experimental task itself promotes orinhibits strategic use of linguistic categories (e.g., Athanasopoulos & Bylund,2013a; Trueswell & Papafragou, 2010; Winawer, Witthoft, Frank, Wu, Wade, &Boroditsky, 2007). In view of the available empirical evidence, it becomes clearthat, instead of asking whether language influences thought or not, we shouldask which cognitive processes are affected by which linguistic categories underwhich circumstances (Athanasopoulos & Bylund, 2013a).

While most of the current research into linguistic relativity has focusedon monolingual speakers, the issue of language and thought in speakers ofmore than one language has up until recently remained peripheral (for recentcontributions, see Cook & Bassetti, 2011; Jarvis & Pavlenko, 2008; Pavlenko,2011).1 This is somewhat surprising, because the finding that language di-versity in grammatical and lexical categories may give rise to crosslinguistic

953 Language Learning 64:4, December 2014, pp. 952–985


differences in cognition could have far-reaching consequences for our under-standing of additional language learning, as it raises a number of importantquestions regarding the interface of language and cognition in the second lan-guage (L2) speaker’s mind. These questions relate to (a) the extent to which L2speakers recalibrate their cognitive dispositions (as indexed by their nonverbalcategorization behavior) toward perceptual phenomena as a result of learninga new language; (b) the transfer phenomena (forward and reverse transfer)that characterize the relationship between L2 acquisition, conceptualization,and cognition; and (c) the linguistic and extralinguistic factors that underpinlanguage-specific cognitive behavior in L2 speakers.

The answer to these questions pushes the boundaries of second languageacquisition (SLA) research to the frontier of knowledge about the cognitiveand linguistic blueprint of the L2 speaker’s mind, especially with regard to thedynamic relationship between the process of L2 learning and the changing cog-nitive state of the L2 speaker. The enterprise of learning a new language mayhave a much greater effect on cognition than has traditionally been conceptu-alized in SLA research. In other words, learning a new language goes beyondthe mastery of the formal linguistic properties and sociopragmatic elements ofa new linguistic system, as it may also entail learning new ways to categorizereality and the observed world, with potentially far-reaching consequences forthe entire cognitive outlook of the bilingual or multilingual speaker.

Using as a starting point the basic methodological and theoretical require-ments as defined in the modern version of the linguistic relativity principle (seeLucy, 1992a, 1992b, 1997), in this article we seek to support the investigationof linguistic relativity in SLA and sketch methodological and theoretical pre-requisites toward developing the domain into a full research program. We offerSLA researchers three theoretical-methodological components that we believeare needed to succeed in this enterprise:

1. We propose a methodology that distinguishes between linguistic relativisticphenomena (i.e., nonverbal behavior) and phenomena related to speechproduction and comprehension (i.e., verbal behavior).

2. We outline the likely cognitive mechanisms at play in the process by whichL2 learning influences nonverbal behavior.

3. We discuss the specific factors that are likely to affect recalibration ofnonverbal behavior in L2 speakers and warrant systematic research in thefuture.

The study of linguistic relativity has been characterized by continuousdebates between, to simplify things, a universalist camp (holding that human

Language Learning 64:4, December 2014, pp. 952–985 954


cognitive processes are not influenced by language but guided by universalperceptual biases) and a relativist camp (holding that human cognitive processesare indeed influenced by language). In the past, the debate was to a large extentuninformed by empirical studies,2 with the consequence that it contained agreat deal of theoretical and sometimes speculative arguments in favor of oneside or the other. Contemporary scholars that engage in the debate on linguisticrelativity instead tend to discuss the significance of the empirical evidenceaccumulated since the 1990s regarding the extent to which our thinking isinfluenced by language and whether such extent is deemed to be large enoughto be considered relevant (see, e.g., Pinker’s view that the documented effects oflanguage on cognition are “trite” and “mundane,” 2007, pp. 126, 135, & 148).In this article, we will not discuss whether relativistic effects are interestingor not, nor how deep the effects of language on thought are: A discussionbased on subjective perceptions and loosely defined criteria does not seem veryfruitful. It is our view that research into linguistic relativity is tremendouslyimportant for our knowledge about the human mind, because it deals with themalleability of human cognition and, more specifically, the possible role thatlinguistic categories play in shaping specific cognitive processes. Therefore,it is also our view that findings that either confirm or disconfirm an effect oflanguage on cognition are equally informative, as they contribute insights intothese matters.

The article is organized in the following way. The next two sections deal withmethodological fundamentals of the study of linguistic relativity, discussing theimportance of nonverbal behavioral data and showcasing nonverbal methodsused in previous studies. Two subsequent sections outline the theoretical un-derpinnings of linguistic relativistic effects in monolingualism and additionallanguage learning. Lastly, we offer an in-depth discussion of the factors thatunderlie cognitive restructuring in the L2 speaker.

Getting a Methodological Requirement Straight: Verbal and

Nonverbal Evidence as Warrants for Different Claims

The distinction between verbal and nonverbal evidence is a cornerstone in thestudy of linguistic relativity. Verbal evidence is behavioral data concerningovert speech production or comprehension, with narrative tasks (e.g., picturedescriptions or film retellings) constituting the most commonly used elicitationtechnique. Nonverbal evidence, in contrast, is elicited through tasks that donot involve overt production or comprehension of speech, such as perception,



classification, sorting, and matching of objects and events.3 The epistemologi-cal importance of nonverbal behavioral evidence to current relativistic researchis evident in the efforts made by scholars to establish a methodology thatcircumvents overt linguistic production and comprehension (e.g., Boroditsky,Fuhrman, & McCormick, 2011; Dolscheid et al., 2013; Levinson, Kita, Haun,& Rasch, 2002; Lucy, 1992b; Roberson, Pak, & Hanley, 2008; Thierry et al.,2009). In an early discussion of the importance of nonverbal behavioral datain relativity research, Lucy (1997) contended that “linguistic relativity is notthe same as linguistic diversity. Without the relation to thought more generally(i.e., beyond that necessary for the act of speaking itself), it is merely linguis-tic diversity” (p. 295). In other words, nonverbal tasks are a methodologicalprerequisite in order to demonstrate effects of language on something beyondthe conscious act of speaking, that is, on thinking itself (for similar arguments,see Casasanto, 2008; Levinson, 1997). Drawing from research on motion eventcognition, we will illustrate the general importance of distinguishing betweenverbal and nonverbal evidence.

Languages across the world exhibit striking differences in the way theyselect and package information about motion. In so-called satellite languages,such as English, information about the manner of motion is typically codedin the main verb, whereas information about the path of motion is coded inthe verb satellite (e.g., an adverbial). A different pattern is found in so-calledverb-framed languages (e.g., Spanish), where the path of motion is coded in themain verb, and information about manner of motion is only optionally codedin an adjunct (e.g., a gerund; Talmy, 2000). Let us suppose that on the basis ofthese crosslinguistic differences, we would conclude that when thinking aboutmotion English speakers are prone to attach importance to manner of motion,whereas Spanish speakers are more likely to attach importance to path. If theonly evidence that we would have for drawing such a conclusion was the factthat Spanish and English speakers differ in the way they package informationabout path and manner of motion in the main verb (such that English speakersuse more manner verbs and Spanish speakers more path verbs), we wouldbe positing differences in nonverbal behavior on the basis of verbal evidencealone. Clearly, such reasoning becomes circular as it conflates the observationwith the explanation (Casasanto, 2008; Greenberg, 1954; Lenneberg, 1953).This was a problem that plagued early relativity studies (Pinker, 2007). Moreimportantly, though, in this particular case an inference based on verbal datawould lead us to an incorrect conclusion: Current research shows that speakersof satellite languages and speakers of verb-framed languages often perceive



and categorize motion along the same parameters (e.g., Gennari, Sloman, Malt,& Fitch, 2002; Gleitman & Papafragou, 2013; Papafragou & Selimis, 2010;Trueswell & Papafragou, 2010; but see Kersten et al., 2010).

The example above shows that effects of linguistic categories on speakingitself (i.e., verbal evidence) are tangentially related to the question of effects oflinguistic categories on nonverbal behavior. Instead, the former kind of effectsis more properly interpreted within the so-called thinking-for-speaking frame-work (Slobin, 1996). As opposed to the studies within the linguistic relativityparadigm, where the focus is on nonverbal behavior, the thinking-for-speakingframework places emphasis on verbal behavior. According to the thinking-for-speaking hypothesis, speakers attend to and verbalize those aspects of realitythat are readily encodable in their language (for a critical discussion, see Athana-sopoulos & Bylund, 2013b). There is a growing body of evidence demonstratingthat speakers of different languages select and structure information differentlyin discourse depending on the lexical and grammatical categories available tothem (e.g., Berman & Slobin, 1994; Verhoeven & Stromqvist, 2001; Jarvis &Pavlenko, 2008).4

It is crucial for SLA researchers interested in linguistic relativity to alwaysrecognize the important distinction between verbal and nonverbal evidence andtheir epistemological consequences. For example, Slobin (1996) is very carefulin pointing out that the thinking-for-speaking hypothesis is not to be confusedwith relativistic positions on language and thought, as it makes no predictionsregarding a person’s worldview or thinking in general. Thus, presenting thethinking-for-speaking framework as a “new” or “weak” version of linguisticrelativity (cf. Han & Cadierno, 2010) appears to be at odds with Slobin’s originalconception. Likewise, interpreting conceptual transfer as evidence of linguisticrelativity on the basis of verbal data alone (cf. Chen, Su, Lee, & O’Seaghdha,2012; Han, 2010) is at odds with the basic methodological premise of linguisticrelativity research. Just like claims regarding thinking-for-speaking must bebased on verbal (and co-verbal) evidence, linguistic relativity claims must bebased on nonverbal evidence.

To date, a large number of studies have investigated thinking-for-speakingphenomena in L2 speakers (see contributions in Cook & Bassetti, 2011;Benazzo, Flecken, & Soroli, 2012; Han & Cadierno, 2010; Jarvis, 2011;Pavlenko, 2011). These studies provide us with important insights into thedifferent processes involved in the acquisition of information structure in anL2. The existing evidence on nonverbal behavior in L2 speakers is, however,comparatively scarce. The consequence of this is that so far very little is knownabout the scope and nature of the effects of additional language learning on



cognitive processing outside of overt verbalization. This evidentiary bias shouldnot, of course, be corrected by replacing verbal approaches to language andthought with nonverbal approaches. Both constitute important lines of inquiryin their own right, and there is no hierarchical relationship or prevalence be-tween them. However, if our knowledge about L2 learning and thought is toinclude cognitive processing outside the act of speaking itself—and thus speakdirectly to the linguistic relativity principle—then it is absolutely necessary toextend the scope of SLA-oriented language and thought research to nonverbalmethodologies.

Addressing Linguistic Relativity Questions Directly:

Methodological Options for Nonverbal Data Elicitation

The methodological framework of modern research into linguistic relativity isanchored on two basic tenets: First, on the proposal that similarity is the basis ofcategorization (Nosofsky, 1986) and, second, that categorization is an essentialelement of human cognition (Harnad, 1987). Against this backdrop, nonverbalbehavior is often operationalized along a continuum of cognitive tasks withan inherent categorization component. These cognitive tasks can be viewed asbelonging to two main types. One type is primarily concerned with so-calledhigher-level cognitive processes, that is, processes that are postperceptual andoccur at a later stage in processing (e.g., categorical judgments, estimations,sorting). The other, more recent type explores lower-level cognitive processes,that is, processes that are automatic and unconscious (e.g., oddball detection,visual search). In addition to showcasing these different methodologies, we willalso discuss the nature of nonverbal evidence itself.5

Higher-Level Cognitive TasksA classic example of a higher-level cognitive task is the triads-matching task,in which the participant is to match a target stimulus with one out of twostimuli alternates, based on their degree of similarity. This task has been usedby a number of studies on the categorization of objects and substances inlanguages with contrasting nominal classification systems. When confrontedwith the task to match one target object with one of two alternates based ontheir common shape or material (e.g., matching a cardboard box with eithera plastic box or a piece of cardboard), speakers whose first language (L1)has obligatory grammatical number marking (e.g., English) tend to matchthe objects on the basis of shape, whereas speakers of classifier languages,where such marking is optional or lacking (e.g., Japanese or Yucatec), prefer



to base their matchings on material (Imai & Gentner, 1997; Lucy, 1992b; seefurther discussion in our later section on theoretical explanations). Researchon L1 Japanese–L2 English bilinguals shows that these object categorizationpreferences may change as a function of learning a language with a differentnominal classification system, in the sense that Japanese speakers of L2 Englishtended to make shape-based similarity judgments significantly more often thanJapanese monolinguals (Cook, Bassetti, Kasai, Sasaki, & Takahashi, 2006;Athanasopoulos, 2007; Athanasopoulos & Kasai, 2008).

The triads-matching paradigm has also been successfully implemented inthe domain of motion by, for example, Bylund and Athanasopoulos (2014) andBylund, Athanasopoulos, and Oostendorp (2013), who investigated the influ-ence of additional language learning on motion event cognition among nativespeakers of isiXhosa and Afrikaans. They used as a starting point the find-ing that speakers of languages with grammaticized imperfective/progressiveaspect are less prone to mention and pay attention to endpoints of motionevents than are speakers whose languages lack such grammatical categories(Athanasopoulos & Bylund, 2013a; von Stutterheim, Andermann, Carroll,Flecken, & Schmiedtova, 2012). Participants had to pair one out of two al-ternate videoclips with a target videoclip on the basis of their degree of goalorientation. Results showed that those Afrikaans and isiXhosa speakers whoused English and other aspect languages more frequently were likely to pairvideoclips with low degree of goal orientation, as was done by English nativespeakers.

Another type of experimental approach is the recognition memory task,which tests the ability to recognize a previously encountered stimulus. In viewof the crosslinguistic difference in the encoding of motion in English andSpanish, Filipovic (2011) implemented a recognition test to investigate memoryof complex events (i.e., three subsequent motion events involving different typesof manner) among bilingual and monolingual speakers of Spanish and English.Results showed that English speakers were better at discriminating between oldand new stimuli where the manner of motion had been manipulated than wereSpanish monolinguals and Spanish–English bilinguals (see also Gennari et al.,2002).

Taking as a starting point the physical foundation of perception (so-calledpsychophysics), recent studies have successfully investigated language effectson the perception of time and pitch (e.g., Casasanto, 2008; Casasanto et al.,2004; Dolscheid et al., 2013). For instance, Casasanto et al. (2004) investigatedthe effects of spatiotemporal metaphors on time estimation. In Greek, as in



Spanish, duration is expressed in terms of quantity (poli ora = ‘much time,’i.e., ‘long time’), whereas in English and Indonesian, duration is expressed interms of distance (i.e., long time). Results showed that English and Indonesianspeakers, as opposed to Greek and Spanish speakers, perceived lines that grewa long distance on the computer screen as having a longer duration than linesthat only grew a short distance (note the duration of the lines was in factidentical). However, when watching animated filling containers, Greek andSpanish speakers were influenced by the quantity with which the containerswere filled, perceiving full containers to have longer duration than half-fullones (again, growth duration was identical). This did not hold for English andIndonesian speakers. The psychophysical paradigm is yet to be extended tobilingual populations.

A challenge that certain relativistic studies are confronted with is thecompatibility between samples drawn from populations with vast culturaldifferences, such as a group of western university students compared to agroup of members of a nomadic semi-literate tribe. Casasanto (2005) andLevinson (2000) among others have discussed the problem of interpretationthat arises from this situation: Cultural variables may confound any observedcognitive crosslinguistic difference. A solution has been proposed in the trainingparadigm, which can help isolate the relationship between linguistic experienceand novel categorical distinctions. In an extension of the time estimation studiesdescribed in the previous paragraph, Casasanto (2008) reports an experimentwhere native English speakers were randomly assigned to perform either a“distance training” or “quantity training” task. Participants had to completefill-in-the-blank sentences using the words longer or shorter for distance train-ing and the words more or less for the quantity training task. Subsequent to thislinguistic training phase, participants performed the nonverbal filling containertask described in the previous paragraph. English speakers who had performedthe quantity training task displayed indistinguishable performance to nativeGreek speakers. Other evidence shows changes in participants’ color categor-ical perception over the course of a training study (Ozgen & Davies, 2002)and effects of conceptual learning on perceptual changes in categorization andobject recognition by adult participants (Goldstone & Barsalou, 1998).

Lower-Level Cognitive TasksThe evidence to date on low-end cognitive processes stem from studies usingEvent Related Brain potentials (ERPs). A case in point is Athanasopoulos andcolleagues’ studies (Thierry et al., 2009; Athanasopoulos, Dering, Wiggett,Kuipers, & Thierry, 2010) on color perception in Greek speakers of L2 English



living in the United Kingdom. Like Russian, Turkish, and other languages,Greek makes an obligatory lexical distinction between light and dark blue(ghalazio and ble, respectively). The researchers adapted a visual oddballparadigm6 where L1 Greek–L2 English bilinguals and English monolingualswere presented with stimuli that differed in color and luminance (lightblue–dark blue, light green–dark green) and shape (squares and circles).Participants were told to press a button when they saw a square stimulus in astream of circles, but received no instruction to attend to the color/luminancedimension of the stimuli. Their brain electrical activity was measured whilethey were exposed to the stimuli. Results showed that the Greek–Englishbilinguals displayed greater visual mismatch negativity (an index of automaticpreattentive change detection, occurring 170–220 milliseconds poststimulus)for the blue rather than the green standard–deviant contrast. The visualmismatch negativity in English monolinguals, in contrast, did not vary as afunction of light/dark blue and light/dark green contrasts.

Crosslinguistic differences in low-level perception have also been found inthe domain of grammatical gender. Boutonnet, Athanasopoulos, and Thierry(2012) elicited behavioral (categorization) and ERP evidence to picture tripletsamong English-speaking monolinguals and Spanish–English bilinguals. Un-like English, Spanish assigns masculine or feminine gender to nouns. In theexperiment, participants watched triples of sequenced pictures and were askedto indicate whether the third picture belonged to the same semantic category(e.g., vegetables) as the previous two. Unbeknownst to the participants, half ofthe triads were designed so that all three picture names shared the same gen-der in Spanish, whereas in the other half the gender of the third picture namewas different from the previous two. Results showed no group differences inthe behavioral performance on the semantic categorization task, but ERPs re-vealed that gender inconsistency triggered a left anterior negative modulation(a response to syntactic violation) in the Spanish–English bilinguals, but notin the English monolinguals. These findings show that the bilinguals automati-cally activated the grammatical category of gender, thus providing support forlinguistic relativity effects in this domain.

Nonverbal Tasks and the Involvement of LanguageA number of studies have set out to investigate the extent to which linguistic rep-resentations are activated in nonverbal tasks. This issue is important because ithelps us to better understand the specific nature of the cognitive processes testedin nonverbal experiments and ultimately the particular ways in which languageinfluences our thinking. The question has been addressed with at least three



different methodologies: verbal interference, transcranial direct current stimu-lation (tDCS), and the laterality approach. In the verbal interference paradigm,a secondary task (e.g., repeating syllables or digits) is added to the primary,cognitive task (e.g., categorizing colors). The underlying rationale is that, ifthe verbal system is simultaneously engaged in a different task, the possibilityto rely on verbal resources to solve the primary task is reduced. Some studiesusing higher-level cognitive tasks have shown that, when a verbal interferencecomponent is introduced, crosslinguistic differences indeed disappear. For ex-ample, Athanasopoulos and Bylund (2013a) showed that, when English andSwedish speakers had to repeat a string of digits while performing a sequencedtriads-matching task of goal-oriented motion events, the crosslinguistic differ-ences attested previously under a noninterference condition disappeared (forsimilar findings, see Gennari et al., 2002; Gilbert, Regier, Kay, & Ivry, 2006;Trueswell & Papafragou, 2010; Winawer et al., 2007).

The tDCS technique is a noninvasive brain stimulation method that can beused to manipulate the access to verbal resources in categorization processes.As such, it is theoretically analogous to the verbal interference method (Perry& Lupyan, 2013). Through weak electrical currents sent through the scalp,cerebral activity in the targeted area is regulated to enhance or reduce (depend-ing on the arrangement of electrodes) a cognitive outcome (e.g., the learningof artificial grammar, De Vries et al., 2009). Lupyan, Mirman, Hamilton, andThompson-Schill (2012) found that by down-regulating activity over Broca’sarea, L1 English speakers exhibited impairments in categorization behavior,such that there was a reduction in their ability to selectively form categories onthe basis of certain perceptual features instantiated in English.7

The laterality approach has addressed the involvement of language in non-verbal tasks by manipulating the visual field in which the experimental stimuliare presented. Based on the premise that the left hemisphere is dominant forlanguage (as right-handedness goes) and that visual fields are contralateralized,these studies examine whether crosslinguistic differences in cognitive process-ing are subject to visual hemifield asymmetries. Findings in the domain of colorindeed reveal that language-specific categorical perception is stronger when thestimuli are presented in the right visual field than in the left (e.g., Gilbert et al.,2006; Mo, Xu, Kay, & Tan, 2011).

Taken together, the findings from these different methodologies indicate thatunder certain conditions linguistic resources are at play inducing a language-specific behavior or response. This is an important piece of evidence that addsto our knowledge about the cognitive architecture of the human mind andthe role of linguistic knowledge in cognitive processing (see the next section



for further discussion). However, the evidence also raises a potential questionconcerning the nature of nonverbal tasks: Could the fact that linguistic resourcesplay some kind of role in the performance on a given nonverbal task be seenas an argument that the task is actually verbal? The answer to this questionis negative. A nonverbal task by definition elicits a nonverbal outcome (thedependent variable often being some sort of categorization of something otherthan words or sentences, such as pictures, videos, objects, color stimuli, etc.)of a high- or low-level cognitive process. The possibility that such a processmight have drawn on linguistic resources does not render the task or the dataverbal—it only demonstrates that language invades our thinking. In fact, theissue at stake is not really whether nonverbal tasks are impervious to linguisticinfluence, but empirically spelling out the extent to which and just preciselyin which ways language intrudes into nonverbal behavior (i.e., the Whorfianproblem). Moreover, the possibility that linguistic resources are present in theperformance of nonverbal tasks does not imply that the degree of languagespecificity found in nonverbal evidence is isomorphic to that found in verbalevidence. For instance, research on motion event cognition (e.g., Gennari et al.,2002) shows that speakers of verb-framed languages may encode informationabout manner of motion around 20% of the time when describing motion,whereas speakers of satellite languages do so 70% of the time; however, whenjudging motion similarity, speakers of satellite languages rely on manner ofmotion 50% of the time, whereas path language speakers do so 30% of the time.It is, in other words, not a given that crosslinguistic differences in the encodingof a given motion feature in language are proportionate to the crosslinguisticdifferences in the encoding of the same feature in memory (Athanasopoulos &Bylund, 2013a; Gennari et al., 2002; Papafragou, Hulbert, & Trueswell, 2008;Papafragou & Selimis, 2010). These are all important empirical matters thatthe three methodologies reviewed in this section can help address.

A Theoretical Premise: The Integrative Nature of Language and

Cognition

Having discussed and showcased the central notion of nonverbal behavior inrelativistic research, we turn our attention in this section and the next to thesecond basic component of a framework of relativistic effects in L2 learning:The need to sketch out a descriptive account of the actual cognitive mechanismsat play and the nature of influence of language learning on nonverbal behavior.An account of the role of additional language learning on cognition needs



to take into consideration three interrelated questions. First, how conceptualknowledge is represented in memory; second, how such knowledge is utilized incognitive tasks to give rise to relativistic effects; and third, what the mechanismis that underpins the influence of language learning on nonverbal cognitiveprocessing. To attempt to answer the second and third questions (discussed inthe next section), one must start with an account addressing the first, that is,delineate the nature of conceptual representation itself, and thus be in a positionto define what is precisely at stake when cognitive change takes place in thelanguage learner.

Neuroscientific approaches to conceptual representation have shown that,contrary to traditional views of mind, language is not a completely separatemodule from other cognitive processes; lexical and grammatical subsystems areconnected with each other and with nonverbal cognitive systems (Pulvermuller,2003). Such a highly interactive account of representation has its origins inbiological neuroscience and is supported by clinical evidence (Humphreys &Forde, 2001). Under this account, conceptual representations are distributedneuronal networks reciprocally linking lexical and grammatical categories totheir visual, action, olfactory, somatosensory, and other attributes (Kiefer &Pulvermuller, 2012). In other words, concepts in the human brain are organizedin terms of distributed representations, such that conceptual representationin memory entails linked sensory (visual, aural, olfactory, etc.), action, andlinguistic-semantic knowledge. For example, when participants process colorwords like green there is unconscious, automatic, and concurrent stimulationof vision and language areas of the brain (Siok et al., 2009). Moreover, whenprocessing nouns such as cinnamon and coffee and verbs like kick, lick, and run,there is stimulation of the expected language areas of the brain, but the latterset of words additionally triggers word-specific somatotopic activation of thesensorimotor cortex (Pulvermuller, 2005), whereas the former set stimulatesolfactory brain areas (Pulvermuller & Fadiga, 2010). The evidence then showsthat concepts refer to multimodal representations that include linguistic andextralinguistic knowledge.

Such an integrated view of language and cognitive processing providesa ready platform for linguistic relativity effects to arise. On the one hand,extra-linguistic experiential elements may account for universals in conceptualrepresentation constrained by basic physiological mechanisms of perception inhumans. On the other hand, because of the multimodal, distributed nature ofconceptual representation, it follows that such representation is open to indi-vidual differences to a considerable extent (Jackendoff, 1990). Indeed, differentmodalities of experience (visual, tactile, auditory, kinesthetic, etc.) contribute to



meaning retrieval to different degrees in different individuals, and concepts canvary in how they are represented in terms of their weighting across the differentmodalities (Warrington & McCarthy, 1987). For example, a nonexperiencedcoffee drinker may have weak or no links to taste and olfactory brain areaswhen processing the word coffee than an experienced coffee drinker. Many in-dividual differences are then a result of variation in biographical characteristicsthat shape and influence an individual’s interactions with the experienced world(De Groot, 2000). A biographical characteristic of particular importance is theparticular language(s) that one is exposed to from birth, and, in the case ofmultilingualism, additional languages learned thereafter. Linguistic experienceis, in fact, a prime candidate to account for some specificity in conceptual rep-resentation due to the fact that languages exhibit considerable variation in howthey lexically and grammatically describe the world and assign prominence tocertain perceptual distinctions therein.

The question then does not so much concern whether linguistic relativ-ity effects will arise or not, but rather the extent to which individuals relyon extralinguistic experiential elements, and the extent to which they rely onlanguage-specific information when performing categorical perception tasks,and why. In fact, the evidence shows that, in the majority of cases, individ-uals rely on both types of conceptual elements (perceptual experiential andlinguistically derived) to perform such tasks. For example, Greek and Englishspeakers are perceptually aware of luminance differences in blue and green,indexed by differential brain activation to different degrees of luminance re-gardless of color. At the same time there is further increased brain activationin Greek speakers for blue rather than green contrasts (Thierry et al., 2009),because Greek has two distinct basic terms to refer to the blue area of colorspace (see earlier discussion). Similarly, to give an example from the grammat-ical domain, the differences between Japanese and English speakers in objectcategorization also mentioned earlier need to be interpreted within a moregeneral pattern of performance, which shows that both groups of speakers arein fact aware of the ontological distinction between objects and substances,because both groups tend to match by common shape more often in a matchingcondition that involves countable object targets, than in a matching conditionthat involves noncountable substance targets (Imai & Mazuka, 2003). Suchphenomena are observed not only with static stimuli such as colors and objects,but also with dynamic ones like motion events (see, e.g., Papafragou et al.,2008; Athanasopoulos & Bylund, 2013a).



Theoretical Explanations: How Do Linguistic Relativity Effects

Arise in L1 and L2, and What Is Their Nature?

How is linguistic knowledge then utilized in cognitive tasks to give rise torelativistic effects? The simple answer comes from the multimodal accountof representation just provided in the previous section: When faced with acategorization task, an individual will rely on all resources of representationavailable, including linguistic ones, to complete the task. In such cases languageis seen as a meddler or an augmenter of categorical perception (Lupyan, 2012;Wolff & Holmes, 2011). Effects of the former type are attested in a study ofmotion events, where eye tracking revealed that observers spontaneously andimplicitly labeled stimuli upon initial observation and subsequently allocatedattention to aspects of the scene not encoded in their respective languages(Papafragou et al., 2008). Effects of the latter type are typically found in colorperception studies, where participants are faster to locate a target among similardistracters when the target also has a different color name than the distracters,rather than just being perceptually different from the distracters (Winaweret al., 2007). That such effects are stronger in the right visual field (which isperceived by the language-dominant left cerebral hemisphere) and that theyare abolished under concurrent verbal interference present solid indicationsof utilization of linguistic information during nonverbal processing (Regier &Kay, 2009).

The examples above are all instances of the online utilization of language,that is, participants/observers access language at the very moment they are mak-ing a categorical decision. In contrast to the online retrieval of linguistic labels,there are also instances where participants rely on language in order to com-plete a subsequent categorization task. Such “thinking after language” effects,as Wolff and Holmes (2011) called them, include experimental manipulations(a) when participants have verbalized stimuli immediately prior to categorizingthem (Gennari et al., 2002), (b) when instructions contain linguistic cues prim-ing participants to respond in language-specific ways (Papafragou & Selimis,2010), (c) when stimuli are presented sequentially instead of simultaneously(Athanasopoulos & Bylund, 2013a), or (d) in a training context (Kersten et al.,2010), the latter two of which involve utilization of working memory to carryout the task successfully. Evidence for the role of language in tasks with aworking memory component comes from dual task paradigms, where crosslin-guistic differences between populations are abolished under a concurrent verbalinterference task (Athanasopoulos & Bylund, 2013a; Trueswell & Papafragou,2010; see the above section on the involvement of language in nonverbal tasks).



How does language learning integrate linguistic information and nonlin-guistic experience to form multimodal conceptual representations? Accordingto Casasanto (2008), to begin to sketch an answer to this question, we needto turn to theories of associative learning. Such theories are anchored on theassumption that representation is integrative, multimodal, with a highly inter-active relationship across modalities, and therefore they would fit the neuro-scientific model of representation outlined earlier. One such theory, Smith andSamuelson’s (2006) Attentional Learning Account (ALA), claims that in theprocess of vocabulary acquisition in L1 development, the role of context isparamount for conceptual category formation. That is, the process of wordlearning entails learning associations between words and the object propertiesthat these words refer to. Children then work out the statistical probability thatthese words will occur in the context of some specific perceptual attributes, bethey visual, auditory, olfactory, and so on. Children are then able to generalizefrom these statistical probabilities and construct multimodal conceptual cate-gories. For example, when presented with a novel noun in the object position ofa verb like break or make (typical for artifacts), with grammatical cues like de-terminers and numerals directly modifying the noun (typical for artifacts) andobligatory grammatical number marking (in contexts of quantification, againtypical for artifacts), in the context of a rigid entity with angular, complexparts (typical for artifacts), children’s attention is typically drawn to the shapeof the object as a cue for category organization, because shape is a commondiagnostic perceptual attribute of the category of artifacts. In contrast, whenpresented with a novel noun in an object position of verbs like pour, eat, or spill(typical for substances), with grammatical cues like determiners and numeralsmodifying not the noun itself, but a unitizer (typical for substances, e.g., shepoured three glasses of water, where glasses serves the role of a unitizer forquantification purposes), in the context of entities with malleable, irregular, andad hoc shapes (typical for substances), children’s attention is typically drawnto the material that the object is made from as a cue for category organization,because material composition is a common diagnostic perceptual attribute ofthe category of substances.

Three design features of associative learning models like the ALA makesuch models ideal candidates for delineating the mechanism underpinning theinfluence of language learning on cognitive behavior. First, associations arehighly context bound, such that the observer/speaker may construe the sameperceptual phenomenon in different ways depending on context (e.g., a muffincues attention to shape but some muffin cues attention to material; Smith &Samuelson, 2006, p. 1340). Second, such associations are also highly open to



individual differences, given that, under this account, categorization behaviorwould be strongly guided by the history of regularities in the individual learner’spast. Finally, and perhaps most crucially, the similarities that characterize anycategory are statistical, not necessary and sufficient (Smith & Samuelson,2006). For example, in a categorization task that requires novel name extensionbased on common shape or material (such as the ones typically used in linguisticrelativity research, e.g., Imai & Gentner, 1997), the computation is not so muchof the kind “go through a list of diagnostic criteria, check the ones satisfied, andwhen enough necessary or sufficient conditions are met, use shape as a basis forcategorisation” (excluding all other possible classification categories like color,texture, material, etc.), but rather “when presented with as many instances ofartifact-like cues in a single combination then it is probable that shape is areliable diagnostic for categorisation” (but not excluding other categories, therelative weight of which is down to an individual’s specific history).

Such reasoning explains a consistently recurring finding in the linguisticrelativity literature that is often interpreted as evidence against the hypothesis(cf. Barner, Inagaki, & Li, 2009); namely, the finding that when cognitivedifferences between populations occur, they are almost never absolute, butalways reflect statistical tendencies toward one pattern, without necessarilyexcluding the alternative basis of classification in individuals. To stay in thedomain of objects, all available studies to date since Lucy’s (1992b) seminalstudy show that preferential categorization by common shape in speakers oflanguages like English, and preferential categorization by common materialin speakers of languages like Japanese and Yucatec, is just that, preferential,such that English speakers will categorize by shape in the majority of (but notall) situations, and vice versa for Japanese/Yucatec speakers. Crosslinguisticdifferences in this and other domains are a matter of relative degree, not absolutebias. As we will argue in the following paragraphs, this is a very importantobservation to make regarding L2 learning, because in the majority of studies,when effects of additional language learning on categorization are found, sucheffects are graded and linear, rather than categorical.

In light of the observations made above, the extent and nature of cognitiverestructuring as a function of L2 learning becomes essentially a matter ofdegree of variation in individual learners’ histories. That is, the degree towhich language learners display convergent and/or language-specific patternsof nonverbal cognition will to a large extent depend on the individual learner’shistory, that is, all the biographical variables that typically characterize speakersof more than one language (as discussed in the next section; Grosjean, 1998;Jarvis & Pavlenko, 2008).



Factors that Affect Cognitive Restructuring in the L2 Speaker

We conclude our review with an empirically informed, in-depth discussionof six factors that have been shown to underlie cognitive restructuring in theL2 speaker, thus addressing the third and final component of our proposedframework for research on linguistic relativity in SLA.

Language ProficiencyThis factor refers to the L2 speaker’s general proficiency with either the L2 orthe L1 (such as in cases of attrition), and in many cases to knowledge of thespecific linguistic property under investigation, because the assumption is thatacquisition of specific semantic distinctions in the L2 may bring about cogni-tive changes in the individual. Such associative learning of the kind we havedescribed would predict that increasing expertise in the L2 leads to cognitiverestructuring in the individual. Indeed, the literature abounds with preciselysuch findings (e.g., Athanasopoulos, 2006; Kurinski & Sera, 2011; Park &Ziegler, 2014). For example, examining the cognitive representation of numberby measuring sensitivity to changes in the number of countable objects or theamount of noncountable substances among Japanese speakers of L2 English,Athanasopoulos (2006) showed that L2 speakers’ behavior in these domainsvaried as a function of general L2 proficiency.

Remarkably, but predictably if associative learning has any explanatorypower in this context, the findings not only show that increase in general L2proficiency may induce cognitive restructuring, but also increases in knowledgeof the specific lexical and grammatical property that is linked to the specificperceptual domain under investigation. For example, increases in knowledge ofEnglish grammatical number marking correlate with increased preference forshape as the basis of categorization in Japanese L2 users of English (Athana-sopoulos, 2007; Athanasopoulos & Kasai, 2008). In this case, the process oflearning the English grammatical number marking system presents the learnerwith statistically more instances of artifact-like cues in a single combination,such that the weight of shape as a reliable diagnostic for categorization isconsiderably strengthened, to the expense of material, which nonetheless re-mains also prominent in some speakers (depending on individual differences inproficiency, etc.), accounting for (a) the very commonly observed in-betweenpattern that bilinguals present relative to their monolingual counterparts and(b) the graded, linear nature of the shift towards the L2. The reallocation of thestrength of the weight of specific categorization cues can also occur as a resultof language attrition. For example, weakening of semantic memory for native



blue terms was significantly correlated with weakening categorical perceptionof native blue contrasts in Greek speakers (Athanasopoulos, 2009).

There are, however, a few studies that have failed to document pro-ficiency effects on nonverbal cognition. Cook et al. (2006), for example,found no effect of L2 proficiency on object categorization preferences inJapanese–English bilinguals. Bylund et al. (2013) also tested the relation-ship between self-assessed global L2 proficiency and motion event catego-rization in L1 Afrikaans–L2 English bilinguals living in South Africa, butfound no effects. A similar result is also reported in Bylund and Athana-sopoulos’s (2014) study on multilingual speakers of isiXhosa. In the domainof color, Athanasopoulos (2009) examined the relationship between generalL2 proficiency and color categorization. This study also failed to document aneffect.

When interpreting the mixed findings on the effects of proficiency on cog-nition it is important to take into consideration that different studies have oper-ationalized this factor differently. Athanasopoulos (2006) and Athanasopoulosand Kasai (2008) used the Oxford Quick Placement Test (OQPT), whereasCook et al. (2006) and Athanasopoulos (2009) used an L2 vocabulary test (Na-tion, 1990). Bylund et al. (2013) and Bylund and Athanasopoulos (2014), incontrast, relied on self-assessed global L2 proficiency. Language proficiency isundoubtedly a complex and multifaceted factor that may not be easily capturedthrough measures that either target a particular component (e.g., vocabulary),or build on global self-reports. Instead, when more sensitive measures of pro-ficiency are used (such as the OQPT or tests of specific proficiency), profi-ciency effects are more likely to become apparent. We adhere to Brown andGullberg’s (2012) observation that the use of standardized proficiency testsacross different studies has a great potential in clarifying the effects of thisvariable and would also allow for postcomparisons between different studypopulations. In addition to establishing general proficiency levels, we believethat careful assessments of participants’ mastery of the specific linguistic prop-erty that gives rise to cognitive differences constitute a promising way for-ward, given that those studies using this approach have all yielded significantresults.

Language ContactThis factor refers to the amount of contact that a bilingual speaker has withhis/her languages. In an associative learning account, the strength of the weight-ings of the elements that make up conceptual representation would be subjectto continuous readjustment as a function of the individual’s language usage



patterns. Under such account, we would predict that frequent usage of a partic-ular language leads to strengthening of language-specific associations, whereasinfrequent usage weakens language-specific associations. The studies that todate have assessed the role of language contact for cognitive restructuring pro-vide empirical support in favor of this interpretation. Athanasopoulos, Dam-janovic, Krajciova, and Sasaki’s (2011) study on color categorization in L1Japanese–L2 English bilinguals measured the role of frequency of L2 use. Thestudy found that the more frequently individuals used the L2, the more theircognitive patterns shifted away from the L1 toward the L2. A similar find-ing was reported by Bylund et al. (2013), who found that the more often L1Afrikaans–L2 English bilinguals used English, the more likely they were tobehave like English native speakers when categorizing motion events. Like-wise, Bylund and Athanasopoulos (2014) reported that L1 isiXhosa speakerswho often spoke languages with grammatical aspect (e.g., English, Sesotho,siSwati) were likely to behave like speakers of aspect languages on a motionevent categorization task.

Apart from the direct influence of language contact, there is another wayin which this factor may influence cognitive restructuring. Research on L2 ul-timate attainment and L1 attrition has shown that the frequency with which alanguage is used may increase or decrease proficiency in that language (e.g.,Bylund, Abrahamsson, & Hyltenstam, 2010; Schmid, 2011). It is therefore rea-sonable to assume that one function of language contact is that of developingor retaining proficiency with the specific linguistic category that presumablyunderlies cognitive restructuring. In this case, language contact would exert anindirect influence on cognition. In order to disentangle the effects of contact oncognition from the effects of proficiency, studies typically assess the interrela-tionship between these factors (see further discussion in Bylund, Abrahamsson,& Hyltenstam, 2012).

The studies to date differ somewhat in their operationalizations of languagecontact: Athanasopoulos et al. (2011) operationalized language contact as aself-reported percentage of L2 use in daily activities; Bylund et al. (2013)used a 5-point scale for self-reported L2 use; and Bylund and Athanasopoulos(2014) relied on self-reports of the percentage of use of typologically similarL2s on a weekly basis. Even though these different operationalizations reducethe possibility that the positive findings reported to date are a methodologi-cal artifact, future research would benefit from working with more nuancedmeasures to investigate the specific nature of language contact. One way for-ward would be to recognize the multifaceted character of this factor, dividing itinto subcomponents according to parameters such as modality (written, aural,



etc.) and interactivity (passive exposure, productive use, etc.; see Bylund &Athanasopoulos, 2015). Such a refinement would also be theoretically mo-tivated, given that, for instance, active and passive contact with a languagecan have differential effects on the development and retrieval of linguisticknowledge (Paradis, 2004). Another way forward would be to more carefullydistinguish between effects of L1 and effects of L2 contact. Some studies todate have assessed either L1 or L2 contact, often based on the assumptionthat the remainder of the time the participant uses the other language (e.g.,Bylund et al., 2013). However, such assumption should ideally be backed upwith further data (see Park & Ziegler, 2014). For instance, in multilingualcontexts it is absolutely necessary to keep track of all the languages spokenby an individual, since inferences about the distribution of contact across L1and L2 cannot be made easily when there are more than two L1s or L2sinvolved.

Context of AcquisitionNo linguistic relativity study has to date systematically manipulated acquisitioncontext to compare, for example, the effects of naturalistic versus instructedlearning on L2 speaker cognition, or the effects of different types of socio-cultural bilingual contexts. In language-specific investigations, studies haveindependently found effects of L2 acquisition both in naturalistic (e.g., Athana-sopoulos, 2009), instructed L2 learning (Kurinski & Sera, 2011), and semi-naturalistic contexts (e.g., multilingual contexts where the L2 is both taughtat school and present at different levels in society; Bylund & Athanasopoulos,2014). Whereas these findings say little about the extent to which differentlearning contexts may produce differential effects on cognition, they demon-strate that cognitive restructuring may indeed occur across a variety of differentcontexts.

Even though the influence of acquisition context on cognition needs furtherinvestigation at present, there is reason to believe that this is a potentiallyimportant factor in several regards, not least because context of learning isinextricably linked to the learning experience itself and to the resulting categoryrepresentations (Smith & Samuelson, 2006). For example, acquisition contextmay function as a variable that modulates the cognitive consequences ofother factors such as age of acquisition onset (as discussed below). Moreover,different acquisition contexts imply differences not only in linguistic input,but also in cultural exposure. An L2 speaker who is immersed in the L2community is exposed to the behavior of the target language speakers, aswell as the environment they interact with. A possible result of this is that the



naturalistic learner to some extent adopts (either consciously or unconsciously)the nonverbal behavior of the target language speaker group, and as suchcognitive restructuring may be facilitated to a greater extent than in cases offormal L2 instruction in an L1 setting, where contact with the target languageculture would be realized only through textbooks and media. At present, eventhough studies provide positive evidence for cognitive restructuring in purelyinstructed settings (Kurinski & Sera, 2011), the relative strength of influenceof different types of learning contexts is yet to be empirically established (for athinking-for-speaking approach to this problem, see Brown & Gullberg, 2011).

Bilingual Language ModeAnother factor that may influence cognitive processing in bilinguals is the de-gree of activation of the L1 and the L2, so-called bilingual language mode.Following Grosjean (1998), the languages of the bilingual are activated to dif-ferent degrees depending on variables such as the linguistic repertoire and code-switching practices of the interlocutor. For this reason, it is possible that in thecontext of evaluating perceptual distinctions, the language mode of the bilingualwill influence his/her categorical judgments. Boroditsky, Ham, and Ramscar’s(2002) study on the categorization of action events by L1 Indonesian–L2 En-glish bilinguals found evidence of such an effect. Here, Indonesian participantswho received the experiment instructions in English exhibited a categorizationbehavior that was more similar to English native speakers than did those whowere tested in Indonesian. A similar pattern of adherence to monolingual be-havior depending on language of experiment instruction was documented inKersten et al.’s (2010) study on motion event categorization. In this study, par-ticipants had to sort novel, animated objects and events into categories on thebasis of manner of motion. Results showed that task performance was sensitiveto language of testing, such that when instructions were given in English, theirbehavior moved toward English patterns, and when instructed in Spanish theirbehavior moved toward Spanish patterns. Filipovic’s (2011) study on recog-nition memory of motion events in Spanish–English bilinguals, in contrast,found no effects of language of instruction (or prior verbalization) on mem-ory performance. In Athanasopoulos’s (2007) study on object categorizationin Japanese–English bilinguals, it was found that the L1-instructed bilingualsdiffered significantly from English monolingual L1 speakers, whereas thoseinstructed in the L2 did not.

Under an associative learning view, effects of language mode on cognitionreflect a contextually cued shift in attention. The language used for experimentinstructions triggers a set of perceptual distinctions learned through and asso-



ciated with that language, thus leading the individual to attend to specific setsof perceptual attributes. The extent to which the L2 speaker is able to attend tothe same perceptual object in different ways as a function of linguistic contextwill depend on the extent to which that person has developed distinct sets oflanguage-specific conceptual representations.

Age of L2 AcquisitionThis factor refers to the age at which additional language learning started. Ageof acquisition may affect cognitive behavior in two different ways. First, it mayinfluence the extent to which bilingual speakers’ cognitive behavior is affectedby bilingual language mode. An example of this is found in Kersten et al.’s(2010) investigation of motion event cognition in Spanish–English bilinguals,mentioned above: Here, it was found that language of task instruction influ-enced the performance of late bilinguals (age of acquisition � 5 years) but notthat of early bilinguals (age of acquisition < 5 years), who displayed similarperformance in both English and Spanish contexts.

From an associative learning point of view, the interaction of learning con-text and age of acquisition is of paramount importance. As Ameel, Storms,Malt, and Sloman (2005) and Pavlenko (2005) have pointed out, early bilin-guals learn their languages in close chronological proximity, and very oftenin a similar learning context, and as such may display compound/convergentpatterns of categorization, drawing upon elements of both the L1 and L2. Laterbilinguals on the other hand learn their languages separated in time, and usu-ally in different contexts, and as such may rely on a less convergent and moredistinct system of representation. As such, one would predict that variation inbehavior as a function of testing context would manifest itself more strongly inlate bilinguals, and this is precisely what the findings of Kersten et al. (2010)show.

Another way in which age of acquisition may influence cognitive behaviorrelates to language proficiency (e.g., Bylund, 2009). Here, age of acquisitionplays the role of a mediating variable in the sense that it affects languageproficiency, which in turn affects cognitive restructuring. This interpretationfinds support in Athanasopoulos and Kasai’s (2008) investigation of objectcategorization in L1 Japanese–L2 English bilinguals. Here it was found thatboth specific L2 proficiency and age of L2 acquisition could predict a changein categorization preferences toward English patterns. However, because thesetwo variables also correlated with each other, subsequent analyses involvingpartial correlations were run. In these analyses, only the effect of specific L2proficiency remained, whereas the effect of age of acquisition was abolished.



Other studies have assessed the effects of age of L2 acquisition (with-out taking into account L2 proficiency or testing context). For example,Boroditsky (2001) examined time conception in L1 Mandarin–L2 Englishbilinguals living in the United States (age of acquisition: 3–13 years). Shefound that speakers with later ages of L2 acquisition were more likely to cat-egorize depictions of temporal succession on the basis of vertical cues (thusadhering to a Mandarin-based categorization pattern), whereas this was lessthe case for those with earlier acquisition ages (for a general criticism of thestudy, see January & Kako, 2007). A marginally significant effect of age ofL2 acquisition was also documented in Bylund and Athanasopoulos’s (2014)study on event categorization among multilingual L1 isiXhosa speakers.

However, some studies have failed to document age of acquisition effects.A case in point is Athanasopoulos’s (2009) investigation of color categorizationin L1 Greek–L2 English bilinguals, whose age of acquisition was 1–13 years.Likewise, no effects of age of L2 acquisition were documented by Bylund etal.’s (2013) study on motion event categorization in L1 Afrikaans–L2 Englishbilingual speakers (age of acquisition range: 3–18 years).

If age of acquisition functions as a mediating factor in language effects oncognition, then the seemingly contradictory findings on this variable reviewedabove might be interpreted in a different light. The participants in Boroditsky’s(2001) and Kersten et al.’s (2010) studies, for example, were naturalistic learn-ers living in an L2 environment. The participants in Athanasopoulos and Kasai(2008) and Athanasopoulos et al. (2011), on the other hand, were more ap-propriately characterized as foreign language learners. The studies by Athana-sopoulos (2009) and Bylund et al. (2013), in contrast, contained L2 speakerswith mixed learner backgrounds: Some were naturalistic learners whereas oth-ers were more properly characterized as foreign language learners, and in somecases it was even difficult to tease apart one category from the other (Bylund &Athanasopoulos, 2014). In view of the fact that age of L2 acquisition onset hasa strong documented effect on ultimate attainment in naturalistic learners butlittle or zero effect in foreign language learners (Munoz, 2006), it is possiblethat the differential effects of this variable found in the studies above may beascribed to context of acquisition. This illustrates the utmost importance of tak-ing learning context into consideration when accounting for age of acquisitioneffects in the context of linguistic relativity.

Length of Immersion in an L2 ContextLiving in a setting where the L2 is spoken as a native language may play a rolein cognitive restructuring, because under an associative learning view, changes



in categorization behavior develop over time, as a function of cumulative ex-perience. In this instance, cumulative experience may entail: (a) proficiencydevelopment, because studies show that, with increasing length of residence,L1 proficiency, and access may decrease and L2 proficiency may increase (e.g.,Linck, Kroll, & Sunderman, 2009); (b) repeated opportunities where the L2speaker is being presented with more (or fewer, in the case of conceptual at-trition) instances of the specific conceptual category in question (see earliersection on Language Contact); and (c) a specific context into which learningcan be grounded, in the sense that the L2 speaker in a conscious or unconsciousway may emulate the nonverbal behavior of the target language community (seealso section on Context of Acquisition). As a result, the weight of preexistingcategories as a basis for categorization would be readjusted, because contextswhere the distinction is relevant and thus salient would become statisticallymore (or less) frequent (see also the above section on language contact).

A number of studies have indeed shown that the longer L2 users haveresided in the L2-speaking environment, the more their cognitive categoriza-tion patterns change. Cook et al.’s (2004) study on object categorization in L1Japanese–L2 English bilinguals, for example, documented a significant differ-ence in cognitive patterns when L2 users were split by length of stay in theL2 country, with one group having spent less than 3 years and the other groupbetween 3 and 8 years. The latter group showed a significant shift towardsthe L2 categorization pattern. Athanasopoulos (2007) found a significant rela-tionship between length of stay and object categorization preferences, but theeffect disappeared when L2 proficiency was taken into account through a partialcorrelation. Athanasopoulos (2009) found independent effects of both lexicalmemory and length of stay (on average 1;2 years) on color similarity judgmentsamong L1 Greek–L2 English bilinguals, suggesting that both factors may in-fluence cognition. Athanasopoulos et al. (2010) revealed neurophysiologicalchanges in preattentive color processing in Greek speakers of L2 English withat least 1.5 years of immersion in the United Kingdom, showing that those L2users with longer immersion periods distinguished less between their nativeblue contrasts than L2 users with shorter immersion periods.

Boroditsky (2001), in contrast, whose L1 Mandarin participants had atleast 10 years of residence in an English-speaking setting, found no signif-icant effects of length of residence on time conception. The possibility thatlength of residence influences cognitive restructuring via language proficiencycan shed some light on the findings of concurrent influence of both variableson cognition, and on the seemingly conflicting findings of Boroditsky. Eventhough research on L2 ultimate attainment and L1 attrition has shown that



length of residence may correlate with acquisition/retention rate, this effect isprimarily observed during the first decade in the L2 context, and past this timeframe length of residence exerts zero or little effect (e.g., Bylund et al., 2012;DeKeyser, 2000; Schmid, 2011). Against this background, the lack of a consis-tent, stand-alone effect of length of residence across studies (whose bilingualpopulations differed substantially with regard to this factor) can be interpretedunder the assumption that (a) length of residence might be intricately relatedto proficiency and (b) effects of length of residence may level out in cases ofprolonged exposure.

As becomes clear from the discussion above, the different factors that influ-ence cognitive behavior in L2 speakers are often intricately interrelated, suchthat, for instance, context of acquisition may regulate the effects of age of L2acquisition, which in turn may regulate the effects of bilingual language mode,and so on. In order to understand the confluence of these factors on cogni-tion, future research must not only carefully scrutinize their interrelationships,but also reliably operationalize them. The commonality of these factors, asmentioned in our earlier discussion of theoretical explanations, is that they areexperiential in nature, relating to, for example, immediate (language mode),cumulative (length of immersion in L2 context), and past (age of L2 acqui-sition) experiences. Currently, researchers often measure these experiences indifferent ways, and the obtained measures are often based on participants’self-assessments. As a result, it is difficult to know whether the lack of corre-spondence between findings is an outcome of instrumentation or whether theinvestigated factor is too weak to be detected at all times. Studies that buildon established methodologies (e.g., validated background questionnaires andstandardized, empirical proficiency measures) will be in a better position topredict the relative consistency of a factor.

Conclusion

In this article, we have outlined three theoretical-methodological componentsnecessary to develop linguistic relativity research in SLA into a full researchprogram. First, we have highlighted the importance of using nonverbal methodsto study linguistic relativity effects in L2 speakers. Here, we argued that theuse of nonverbal tasks is necessary in order to avoid the circularity that ariseswhen inferences about nonverbal behavior are made on the basis of verbalevidence alone. Second, we have identified and delineated the likely cognitivemechanisms underpinning cognitive restructuring in L2 speakers by integrating



a theoretical framework (ALA) from the field of cognitive psychology intothe field of SLA. By doing so, we have demonstrated that the extent andnature of cognitive restructuring in L2 speakers is essentially a function ofvariation in individual learners’ trajectories. Third, we have offered an in-depthdiscussion of the factors that characterize those trajectories, anchoring themto the ALA, and reinterpreting their relative strength in predicting L2 speakercognition.

As a final remark, we wish to emphasize that the fields of SLA and relativityresearch have a tremendous potential for cross-fertilization The heterogeneityand dynamic nature of multilingualism can provide a rich source of data,both in terms of elucidating the linguistic and extra-linguistic factors thatunderpin differences between humans, but more importantly, of bridging thegap between observed effects of perceptual training in the laboratory, andthe ecological validity of such effects to real-life instances of novel categorylearning, of which L2 learning is an example par excellence. An approachto language and thought in L2 speakers that builds on the solid knowledgebase of additional language learning offered by SLA research and, moreover,relies on a methodological paradigm processed through the sensibilities ofrelativity research, could maximize the real-world generalizability of cognitivemechanisms of perceptual learning and readily provide a practical context forany proposed research on language and thought to flourish. It is for this reasonthat the study of relativistic effects within an SLA context holds the greatestpromise in terms of discovering the holy grail of cognitive science, that is, thecontent and origin of our thoughts.

Final revised version accepted 30 April 2014

Notes

1 We occasionally use the phrase “language and thought” to refer to the broader fieldof study concerned with the relationship between human language and thought, beit via verbal (e.g., Slobin, 1996), nonverbal (e.g., Lucy, 1997), or evenintrospective/linguistic descriptive methods (e.g., Lakoff & Johnson, 1980).

2 According to Lucy (1997), only half a dozen empirical investigations on linguisticrelativity were carried out up until the 1980s.

3 A third type of evidence can also be distinguished, so-called co-verbal data, whichconcern behavior concurrent to speech production, such as gesture and visualattention allocation (for an overview, see Gullberg, 2011).

4 In the interest of space and coherence, we leave out an extended discussion of thethinking-for-speaking hypothesis.



5 We will mostly delimit our review to research that has found positive evidence ofcrosslinguistic differences in cognition and thus is of potential relevance foradditional language learning.

6 In a visual oddball task, which is commonly used in cognitive andneurophysiological studies, the participant responds to target stimuli that arepresented infrequently and irregularly within a series of frequent or standard stimuli(Huettel & McCarthy, 2004, p. 379).

7 Although the tDCS technique offers plentiful possibilities, the findings in Lupyanet al. (2012) should be interpreted in view of the fact that the participants wereexplicitly provided with verbal labels in the categorization task and were thusprompted to resort to language for task completion.

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