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International Journal of Multilingualism
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Recognising words in three languages:
effects of language dominance and
language switching
a
Xavier Aparicio & Jean-Marc Lavaur
b
a
Laboratory Vision Action Cognition – EAU01, Institute of
Psychology, University of Paris Descartes, 92100, BoulogneBillancourt, France
b
Laboratory Epsylon, EA 4556, University of Montpellier 3, Place
Albert 1er, 34000, Montpellier, France
Version of record first published: 28 Mar 2013.
To cite this article: Xavier Aparicio & Jean-Marc Lavaur (2013): Recognising words in three
languages: effects of language dominance and language switching, International Journal of
Multilingualism, DOI:10.1080/14790718.2013.783583
To link to this article: http://dx.doi.org/10.1080/14790718.2013.783583
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International Journal of Multilingualism, 2013
http://dx.doi.org/10.1080/14790718.2013.783583
Recognising words in three languages: effects of language dominance and
language switching
Xavier Aparicioa* and Jean-Marc Lavaurb
a
Laboratory Vision Action Cognition EAU01, Institute of Psychology, University of Paris
Descartes, 92100 Boulogne-Billancourt, France; bLaboratory Epsylon, EA 4556, University of
Montpellier 3, Place Albert 1er, 34000 Montpellier, France
Downloaded by [Xavier Aparicio] at 09:36 28 March 2013
(Received 6 November 2012; final version received 20 February 2013)
This study aims to examine language dominance and language switching effects in a
series of monolingual and multilingual lexical decisions in which participants have
to decide if the presented letter string is a word or not, regardless of language. Thirty
participants (12 FrenchEnglish bilinguals and 18 FrenchEnglishSpanish
trilinguals) were recruited for two different experiments. In Experiment 1, 12
bilinguals processed two monolingual lists (L1 and L2) followed by a bilingual list
(with L1 and L2 words). The results indicate faster answers and better accuracy for
L1 words compared to L2 words in both lists, and a general slowdown of processing
in the bilingual list, highlighting language switching effects (switch from L2 to L1
faster than from L1 to L2). In Experiment 2, 18 trilinguals performed successively
monolingual (L1, L2 and L3), bilingual (L1L2, L1L3 and L2L3) and trilingual
(L1L2L3) lists. The results show a slowdown of word processing as a function of
number of languages involved, even for the dominant language (L1). Moreover, a
language switching effect was found for all multilingual lists, in larger proportions
when the list involves the two weakest languages (L2 and L3). Results are discussed
in the light of interactive models of bilingual visual word processing.
Keywords: trilinguals; visual word recognition; lexical decisions; switching cost;
language dominance; language repetition; BIA-d
Introduction
In psycholinguistic research, it has been well demonstrated that the act of reading
words, in any known language, involves cognitive processes in which the reader
matches a representation of the incoming orthographic information of a given word
with the words he/she knows, stored as abstract form representations in an entity
called the mental lexicon (van Heuven, Dijkstra, & Grainger, 1998). The mental
lexicon is familiarly compared to a huge database, containing not only the words
known by a person, but also all their lexical characteristics, such as orthography,
phonology, semantics and language information. Retrieving information about a
word (i.e. the words identity and a useful understanding of the word) is also defined
by researchers as lexical access (see Dijkstra, 2005). If lexical access appears to be an
easy notion at first glance, complications arise as within a language one incoming
word could activate several candidates before being identified. The situation reaches
a higher level of complexity when lexical access involves multilinguals, as in this case
*Corresponding author. Email: xavier.aparicio@parisdescartes.fr
# 2013 Taylor & Francis
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X. Aparicio and J.-M. Lavaur
several lexical candidates from different languages could be activated by the input
word (Dijkstra & van Hell, 2003; Lemhöfer, Dijkstra, & Michel, 2004; van Heuven
et al., 1998). Lexical access is the crux of much research on multilingualism, and
most of the researches agreed to consider the access to the mental lexicon as nonselective, leading to interferences between the languages known. Basically, it seems
that all possible word candidates from the different languages are activated during
word processing, independently of the language they belong to (Font & Lavaur, 2004;
Lemhöfer et al., 2004; Orfanidou & Sumner, 2005). According to Midgley, Holcomb,
and Grainger (2009), word recognition is modulated by bilinguals’ proficiency,
depending on frequency of language use and Age of Acquisition (AoA). In case of
late learners of an L2, proficiency is often asymmetrical, ranging from the L1 to the
last language acquired. The hypothesis of an integrated lexicon also raises the
question of language dominance (the mother tongue in most cases, or the L2 if it
reaches a higher level of proficiency) and language switching, and the eventual costs
elicited by switching from one language to another.
Word recognition in multilinguals
According to Dijkstra and van Hell (2003), multilinguals are most often led to speak
or read in one given language, and to do so, it is necessary to reduce interference with
their other languages. The capacity of control by multilinguals on the relative
activation of their different lexicons seems to be quite limited (Christoffels, Firk, &
Schiller, 2007). Nevertheless, for people able to speak several languages, it is
sometimes useful within a conversation to use words belonging to a language
different from the one being used (Meuter, 2005; Moreno, Federmeier, & Kutas, 2002).
Moreno et al. (2002) suggest that the unintended intrusion of a word from a language
different from the one initially spoken is often due to a problem of retrieval of the word
in the initial language, leading to the substitution of a homologue (translation
equivalent) from another known language, in order to retain the meaning. For the
person detecting the language switch, it is difficult to process a word from the new
language, primarily because the word is unexpected and the language used is irrelevant
in the communication context. In a recent study, Aparicio et al. (2012) have
highlighted N400 differences between the three languages known by a trilingual
during a semantic categorization task involving words in three languages. Participants
were asked to read silently the presented words and to press a key on a remote control
if the word was the name of an animal (e.g. dog). Words were presented in a mixed list
including French, English and Spanish words, allowing the authors to study language
switching effects. Their results indicate that the native language (L1) possesses a very
specific status within the brain compared to L2 and L3, meanwhile the larger
amplitude of the N400 for L3 words compared to L2 words is supposed to reflect the
difference of proficiency between these later acquired languages. According to these
findings, we assume that language switching costs depend on the number of languages
involved in the switch, and more precisely that language switching will be influenced
by the relative dominance of one given language upon the other languages known.
Language switching costs
Regardless of language proficiency in each language, language switching ability is not
constant and relies on individual ability to switch in a given context (reading,
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International Journal of Multilingualism
3
speaking). Many researches (Chauncey, Grainger, & Holcomb, 2008; Christoffels
et al., 2007; Grainger & Beauvillain, 1987; Macnamara, Krauthammer, & Bolgar, 1968;
Thomas & Allport, 2000) focused on the eventuality of a cognitive cost elicited by
code switching. The researchers argue in favour of a switch cost; however, a debate
still exists to determine whether the cost is due to a comprehensive mechanism of
task control, or to specific processes of language control in multilinguals (Chauncey
et al., 2008). According to the developemental version of the Bilingual Interactive
Activation (BIA) model (an extension of BIA model also based on Revised
Hierarchical Model (RHM) model, see Grainger, Midgley, & Holcomb, 2010), the
cost of language switching is attributed to a mechanism, a language node, controlling
the relative activation of each lexical representation per language. Language nodes in
the BIA worked as a control mechanism of attention and of the task proposed in
models of cognitive control (Chauncey et al., 2008).
According to Chauncey et al. (2008), when learning a second language, bilinguals
may develop a general cognitive control mechanism permitting to supervise the
activation of representations of each language. The BIA-d postulates that
the processing cost of a language switch is the result of descending inhibition from
the inappropriate language node to the lexical representations of the target language.
Grainger and Beauvillain (1987; see Thomas & Allport, 2000 for similar findings)
observed switch costs elicited by language switching in a generalised lexical decision
task. In this study, participants responded to items in two monolingual lists, in which
items from one language were presented, and in a bilingual list in which French and
English items were mixed. In this task, the language to which the stimulus belongs to
was supposed to have no consequences on the required response. Nevertheless, the
authors demonstrated that this information was not ignored. In the bilingual list,
the response time for the lexical decision for a given language was slower when the
preceding trial belongs to the other language. Thus, it seems easier to switch from the
dominant language to the non-dominant language than the contrary.
The present study
The aim of this research is the study of language dominance and language switching
effects in trilinguals. We based our framework on the one used by Grainger and
Beauvillain (1987) but adding one language, using several lexical decision tasks with
bilinguals and trilinguals. We assume that the addition of a third language will allow
us to better understand the different connections between the languages, given that
most bilinguals speak a third language. It will also help us to determine the nature of
the links (lexical or conceptual) bounding languages within the mental lexicon. In
this purpose, we recruited 30 participants, 12 FrenchEnglish bilinguals and 18
FrenchEnglishSpanish trilinguals.
Our first aim is to estimate the dominance effect between different monolingual
lists (constituting a baseline for each language in terms of lexical access) and in
multilingual lists including two or three languages. According to the findings of
Grainger and Beauvillain (1987), the response time in a bilingual list (two languages
involved) is slower than in monolingual list (one language involved) due to language
switching. All languages are expected to be slowed down in multilingual conditions,
but dominance effect is supposed to remain, given that language competition would
be in favour of the dominant language. Nevertheless, some attenuation of dominance
could occur due to the difficulty of processing two or three languages simultaneously.
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4
X. Aparicio and J.-M. Lavaur
The general prediction is that monolingual lexical decision would be faster than
multilingual lexical decision for all languages. Based on previous findings, we
assumed that switch costs are higher for non-dominant languages (L2 and L3). In
addition, we expect word recognition to be slower as a function of number of
languages involved. We predict that L1 would have a higher level of activation
compared to the two other languages. Moreover, given that participants’ L3 was
learned consecutively to L2, L2 is predicted to be activated more easily than L3 as
participants are expected to be more proficient in L2. In the bilingual lists, we aim to
determine the cost of language switching in all combinations of languages, and we
expect switching between L2 and L3 to be slower than other switch directions.
Indeed, the route between these languages is rarely used, and probably required a
necessary activation of L1 nodes. Consequently, we assume that in trilingual
memory, L1L2 and L1L3 connections are often solicited in purpose of
communication, but L2L3 links are supposed to be weaker, which may result in a
higher switch cost. In trilingual lists, we expect larger switch effects compared to
bilingual conditions, because of many combinations of switches and unusual
language changes. Moreover, in multilingual lists, we will compare repetition (target
preceded by a word in the same language) and switching trials (target preceded by a
word in a different language).
Experiment 1: lexical decisions in two languages
In the first experiment, we compare the processing of words specific to one language
(no orthographic overlap between translation equivalents in the three languages). We
select FrenchEnglish bilinguals, with a high level of competence in L2, and record
their answers in a series of lexical decisions in which words are presented in one
language only (monolingual list), or two languages (bilingual list). Our objective is to
evaluate the effects related to language switching when two languages are presented
within the same list of stimuli (Grainger & Beauvillain, 1987), in order to ultimately
compare the results to those obtained when a third language is introduced.
Participants performed several lexical decisions involving one or both languages
known by the participants. When a word belonging to L2 is presented consecutively
to L1 trial, we assumed that L1 lexicon has to be inhibited (strong inhibition because
L1 processing is automatic) and the inhibition previously settled on L2 has to be
overcome. This switch is expected to require more time, because L1 has been strongly
inhibited, and consequently it would be more difficult to overcome the inhibition. In
language repetition (L1 word following a L1 word, and L2 word following a L2
word), the BIA-d predicts that the word would be identified faster, because the
corresponding language node has been already activated by the preceding item, and
its degree of activation is really high.
Methods
Participants
Twelve FrenchEnglish bilinguals (mean age23.9), students of English at the
University of Montpellier 3 (France) were recruited. All were native speakers of
French, and spoke English as a second language. They had to fill in a questionnaire
to determine their skills in both languages (see Table 1). After the experiment, they
International Journal of Multilingualism
5
also had to perform a post-test translating French words into English to ensure that
they had a sufficient knowledge of the words used in the experiment.
Table 1 shows answers to the linguistic skills questionnaire for L1 and L2. The
results indicate that participants consider themselves more proficient in L1 compared
to L2 t(11) 8.95, pB0.001. Moreover, a t-test shows that performance on post-test
ranged from 77% to 100% correctness in English with a mean of 89% (SD 0.15).
Table 1. Self-evaluation (SD in parenthesis) of linguistic skills of the participants of
Experiment 1 in French (L1) and English (L2) on a 7-point Likert scale and AoA of English
(in years).
Languages
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Language skills
Reading
Oral understanding
Speaking
AoA (years)
LI French
7.0 (0.0)
7.0 (0.0)
7.0 (0.0)
L2 English
6.8
6.0
6.1
9.9
(1.2)
(0.8)
(1.0)
(1.1)
Stimuli
All words were non-cognates, with no orthographic overlap with their translation
equivalent in the other language. Seventy words were selected per language, with length
in between three and eight letters, a mean frequency in occurrences per million (OPM)
of 89 (SD23) for French (Lexique 3, New, Pallier, Brysbaert, & Ferrand, 2004) and 93
(SD26) for English (CELEX, Baayen, Piepenbrock, & Gulikers, 1995). Seventy
pseudo-words were created for each language (total 140) with the WordGen software
(Duyck, Desmet, Verbeke, & Brysbaert, 2004), in order to match in terms of length, and
be pronounceable letter strings. Controls have been made to ensure that words and
pseudo-words had few orthographic neighbours and were not interlingual homographs.
Apparatus and procedure
Participants were seated in a sound attenuated room in front of a computer screen.
For each trial, they had to decide if the presented letter string was a word or not,
regardless of language (either L1 or L2), and manually press a response button on
the keyboard. Stimuli were displayed on the centre of the screen with E-Prime
software (Schneider, Eschman, & Zuccolotto, 2002), in white ink on a black
background. An example of a trial sequence is provided in Figure 1.
In the first part of the experiment, the participants were presented with two
monolingual lists sequentially in a counterbalanced order (L1 then L2, or L2 then L1).
The bilingual list (two languages) was performed after two monolingual lists. The stimuli
were presented in a pseudo-randomised order, to get as much repetition as switched
trials, and making the next trial unpredictable (in terms of language belonging).
Results
The data analysis was performed for errors and reaction times (RTs) on correct
answers. RTs less than 200 ms and greater than 1500 ms (3% of the data) were
6
X. Aparicio and J.-M. Lavaur
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excluded. Analyses of variances (ANOVAs) were performed to compare the results
for each language in different experimental conditions.
Figure 1. Presentation of an experimental sequence. The French word VOITURE (car) is
followed by an ISI, then by a fixation point preceding the next English trial HOUSE.
List context effects (number of languages)
In this section, we compared performance to the same set of words in each language
(L1 and L2) as a function of the number of languages in the list (1 or 2). ANOVAs
were performed on the RT and percentage error data, with target language (L1 and
L2) and list context (1 or 2 languages) as within subject factors.
In the RT analysis, there was a main effect of target language F(1,11) 16.12,
pB0.01, with French words processed faster (509.1 ms, SD 53.8) than English
words (569.8 ms, SD51.1), regardless of list context. Moreover, the analysis also
revealed a main effect of list context, F(1,11) 5.32, p B0.05, indicating that the
introduction of another language slows down the processing of words. Nevertheless,
the interaction between these two factors was not significant (F B1), reflecting the
fact that list context effect was quite similar for both languages. Indeed, the
cumulative effect of the number of languages was about 36 ms for L1 words
F(1,11) 4.18, p B0.05, and 30 ms for L2 words F(1,11) 4.68, pB0.05 (see
Figure 2).
In the error analysis, there was no main effect of language (FB1), but a
significant main effect of list context F(1,11) 5.30, pB0.05, indicating that the
presence of two languages in the list elicits more errors. The interaction between
these two factors was not significant (F B1).
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International Journal of Multilingualism
Figure 2.
7
Mean RT (ms) for words in L1 and L2 in pure and generalised lexical decisions.
Within-list language switching effects
In these analyses, we compared performance to words in both languages (L1, L2)
presented in the bilingual list as a function of the language of the preceding trial.
ANOVAs were performed on the RT and error rates data with target language (L1,
L2) and language switch (switch vs. repetition trials) as main factors. Additional
analyses compared performance as a function of the direction of the switch (L1
preceded by L2, or L2 preceded by L1).
In the RT analysis, there was a main effect of target language F(1,11)11.91, pB
0.01, indicating that French words (527 ms) were processed faster than English words
(587 ms). Moreover, we found a main effect of language switch F(1,11)10.51, p B0.01,
reflecting that words preceded by a trial in the same language were processed faster
(language repetition 536 ms) compared to targets preceded by a trial in the other language
(language switch, 574 ms). Here again, the interaction between these two factors was not
significant (FB1), indicating that switch effect is quite similar for both languages.
This could be explained by the fact that for L1 targets, the difference between
repetition and switching condition was not significant F(1,11) 2.26, p1. Nevertheless, we obtain a significant effect F(1,11) 4.58, p B0.05 when comparing L2
targets in repetition (562.8 ms) and switching (607.1 ms) conditions. Interestingly,
when focusing on language switching direction (L1L2 or L2L1), target words were
processed more slowly in L1L2 direction compared to L2L1 direction F(1,11)
25.54, p B0.001, which highlights an asymmetry between languages (Grainger &
Beauvillain, 1987; Kroll & Stewart, 1994; Von Studnitz & Green, 1997). As we can
see in Figure 3, L2 words were processed significantly slower than L1 targets,
regardless of the preceding trial. It also seems that language switching cost is greater
towards the non-dominant language, i.e. L1L2.
Discussion
The aim of this experiment was to study language switching effects, knowing that
they rely on the degree of proficiency in both languages. The results obtained are
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X. Aparicio and J.-M. Lavaur
Figure 3. Mean RT (ms) for French and English target words depending on the repetition or
switching condition in the generalised lexical decision.
similar to those from Grainger and Beauvillain (1987) reflecting that cost combined
with language switching is demonstrated for all languages, but larger when switching
from the dominant language to the non-dominant language. This cost seems
modulated by the level of activation of the different languages, as predicted by the
BIA-d model.
Language dominance effects
Both monolingual lexical decisions (L1 and L2) clearly show language dominance
effects, with L1 words processed faster than L2 words. This dominance of L1 is also
demonstrated in the bilingual lexical decision (L1L2), with somehow a slowdown of
processing in both languages compared to monolingual lists. This slowdown could be
explained by a lateral inhibition of units from the inadequate lexicon (Grainger &
Beauvillain, 1987; van Heuven et al., 1998). According to the BIA-d (Grainger et al.,
2010), when a candidate from a language is activated, the phenomenon of lateral
inhibition is applied to words belonging to the other languages spoken, reducing
interferences between the lexicons. Switching from L1 to L2 supposes a deactivation
of the L1 lexicon in order to activate the L2 lexicon, which represents a more
complex processing.
Language switching effects
The consecutive presentation of words belonging to different languages constraints
participants to process several language switching possibilities, from L1 to L2 and L2
to L1. The observed switch cost is 30 ms in L2L1 direction and 45 ms in L1L2
direction, indicating that the switch cost is larger from the dominant language to the
weaker one. These results are in line with previous findings in the literature (Grainger
& Beauvillain, 1987; Von Studnitz & Green, 1997). The processing of the trial
preceding the language switch supposed a competition between the lexical units
activated, and consequently it requires the intervention of an inhibition mechanism.
The presentation of a L1 word is supposed to activate more representations
compared to L2, and requires a stronger inhibition which will slow down the
International Journal of Multilingualism
9
activation of the last presented L2 word. It could also explain the asymmetry
observed during language switching.
Our objective in the second experiment is to determine to what extent these
language switching effects or more specifically the cost associated to language switch
relies on the asymmetry of the lexical units in three languages.
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Experiment 2: lexical decisions in three languages
Experiment 2 is settled to examine language switching effects when the three
languages known by the participants are involved. As in Experiment 1, target words
are presented in a monolingual, bilingual and also a trilingual condition with words
from the three languages. Here, we assume that if similar differences in processing are
highlighted for the same words in these conditions, this could mean that the
activation of the three lexicons simultaneously requires a higher degree of control in
order to activate the relevant lexicon and inhibit non-target languages. Specifically
for the trilingual list, we assume that interferences between these languages are more
important compared to the other conditions. Because of language switching trials in
the multilingual lexical decision, we expect (as reflected in the first experiment
results) an overall slowdown of processing modulated by the number of languages
involved in the task, keeping in mind that the modulation of the effects could be due
to the dominance (or non-dominance) of the language concerned. These effects
could also be modulated by the succession of activation-inhibition mechanisms
involved during language switching processing.
First, the expected effect of language dominance should be observed for the three
monolingual lists (in French, English and Spanish, respectively), because
the recognition of the shape of the word depends on the degree of proficiency in
the presented language. This result is in line with the patterns of results obtained by
Aparicio et al. (2012) with trilinguals, and corresponds to the activation of the N400
component. Moreover, according to Experiment 1, this effect could be generalised to
all the languages involved, in monolingual and multilingual lists. Even if we expect a
general slowdown of processing due to language switching, words belonging to the
dominant language (French L1) should be processed faster than in the other
languages. Indeed, the degree of activation of shapes and semantics is linked with the
degree of proficiency in the different languages, at least at the start of the processing.
Concerning L2 (English) and L3 (Spanish), we assumed the degree of activation of
their lexical units to be weaker, and the control exerted on language switching to be
harder to apply, with nevertheless an advantage of L2 above L3.
Here, paired comparison between languages should give us more information on
the dominance and the organisation of languages in the memory (Font & Lavaur,
2004; Thomas & Allport, 2000). Finally, by considering the slowdown observed in
Experiment 1 to be due to the presence of two languages, we would be likely to
observe an increase of these effects when participants have to process consecutively
words from three languages, because of the complexity of language combination.
Indeed, some language switches could be used less than others (i.e. from L2 to L3
and vice versa), depending on the context of use. We assumed the effects relying on
language switching to be modulated by the number of languages involved in the
lexical decision. More specifically, language switching should be modulated on one
hand by the direction of the switch (e.g. L1 to L3 vs. L3 to L1), and on the other
hand by the proficiency of the participants in the three languages. According to the
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X. Aparicio and J.-M. Lavaur
BIA-d model (Grainger et al., 2010), associated with previous findings, the cost
associated to language switching is higher from the dominant language to a nondominant language (see Experiment 1).
The study of the links between the second L2 and the third L3 languages has been
barely submitted to experimentation so far. Switching between these languages could
be a problem if we consider its small probability of occurrence and requires
conceptual mediation by the L1. According to the BIA-d, for these two nondominant languages, we should observe results similar to Experiment 1 for L1 and
L2, that is to say a slower processing of words from a non-dominant language, and a
larger cost in L1L2 direction. Switching involving L1 and L3 should highlight similar
patterns of results, with nevertheless longer latency for L3 words, given that
participants have learned this language later in life and thus, they are supposed to
have a lower degree of control of this language. Finally, concerning the two nondominant languages (L2 and L3), we expect a global slowdown of processing because
these two languages are acquired later in life compared to L1. Considering the results
of Experiment 1, we may observe a cost associated to language switching larger in
L2L3 direction compared to L3L2 direction, if a kind of hierarchy is reflected also on
the level of activation of the two non-dominant languages.
Method
The experiment included a series of seven lexical decisions involving the three
languages known by our participants. First, participants were presented with three
monolingual lists with words and pseudo-words matched per language (respectively
L1, L2 and L3). In a second part they were shown three bilingual lists including
words from two known languages and pseudo-words matched these languages
(respectively L1L2, L1L3 and L2L3); finally, a trilingual list including all the
languages known by our participants and pseudo-words matched from all three
languages (L1L2L3) was presented.
Participants
Eighteen students of Foreign Language Studies at the University of Montpellier 3
(France) were recruited, native speakers of French, speaking English as a second
language and Spanish as a third one (mean age24.3). They filled in the same
questionnaire and post-test as in Experiment 1. Main results of the questionnaire are
presented in Table 2. A t-test shows that performance on post-test ranged from 72%
to 100% correctness in English with a mean of 86% (SD 0.11), and from 59% to
Table 2. Results of the linguistic abilities questionnaire and AoA in the three languages
(French L1, English L2 and Spanish L3) on a 7-point Likert scale (SD in parenthesis).
Languages
Language skills
Reading
Oral understanding
Speaking
AoA (years)
LI French
6.9 (0.1)
7.0 (0.0)
7.0 (0.0)
L2 English
6.2
6.0
6.0
9.8
(0.2)
(0.5)
(0.4)
(1.2)
L3 Spanish
5.8
5.2
5.1
13.6
(0.9)
(0.6)
(0.4)
(1.0)
International Journal of Multilingualism
11
93% correctness in Spanish with a mean of 77% (SD 0.15). Performance was
significantly better in English than in Spanish (t (17) 4.3; pB0.05.)
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Stimuli
For each known language, 140 non-cognate words were selected from a multilingual
lexical database (Laxén, Aparicio, & Lavaur, 2008). Monolingual lists in L1 and L2,
as well as the bilingual list L1L2 were identical to Experiment 1, but additional
items were selected in order to have an equal number of words in each list. Every list
is made up of 60 words and 60 non-words. In all the lists (monolingual and
multilingual), there are as many words as non-words. For instance, there were 60
French words in the pure list, 30 French words in mixed lists in two languages and 20
French words in the list involving the three languages. The words from the other
languages were also shared out this way. All pseudo-words were pronounceable
strings of letters in their respective languages.
Apparatus and procedure
Apparatus was similar to Experiment 1. Procedure was slightly modified to avoid a
bias of list orders, and the experiment was divided in three sessions. In the first part,
three pure lists were established, one in each language. All participants were
presented with three monolingual lists, in various order. In the second part,
participants responded words and pseudo-words from two languages. In these
bilingual lists, items were presented in a random order in a way that the language of
the next item was unpredictable. Again, three lists were established: FrenchEnglish
words and pseudo-words (L1L2), FrenchSpanish words and pseudo-words (L1
L3), and EnglishSpanish words and pseudo-words (L2L3). The order of
presentation of these three lists was counterbalanced across participants. The
number of switches in each direction was the same as the number of repetitions.
Finally, participants performed a trilingual list with words and pseudo-words from
the three languages (L1L2L3). The items were randomly mixed to form a list.
The number of switches in each direction was the same as the number of repetitions.
The presentation of words and pseudo-words was controlled to ensure that a given
item was presented only once to a given participant in the whole experiment.
Results
The data analysis was performed for errors and RTs for correct answers. RTs less
than 200 ms and greater than 1500 ms (4% of the data) were excluded. ANOVAs were
performed to compare the results for each language in the different experimental
conditions.
List context effects (number of languages)
Here we compared performance to the same set of words in each of the three
languages (L1L3) as a function of the number of languages in the list (13
languages). ANOVAs were performed on the RT and percentage error data with
target language (L1L3) and list context (1, 2, or 3 languages) as main factors.
Downloaded by [Xavier Aparicio] at 09:36 28 March 2013
12
X. Aparicio and J.-M. Lavaur
In the analysis, there was a main effect of target language for RTs F(2,34) 24.93,
pB0.001 and errors F(2,34) 19.24, pB0.001. French words were processed faster
than English words F(1,17) 9.86, pB0.001 and elicited less errors F(1,17) 5.42,
pB0.01, and also than Spanish words for RTs F(1,17) 10.40, pB0.001 and errors
F(1,17) 7.24, p B0.01. Concerning the two non-dominant languages, L2 words
were processed faster than L3 words F(1,17) 54.27, pB0.001. The analyses also
highlight a main effect of list context for RTs only F(2,16) 3.13, pB0.05, indicating
that monolingual lists were processed faster than bilingual F(1,17) 4.58, pB0.05
and trilingual lists F(1,17) 6.34, p B0.05. Details are provided in Figure 4.
There was also a significant interaction between list context and language,
F(2,16) 3.40, p B0.05, with different list context effects for words in L1, L2, or L3.
For L1 words, there was a cumulative effect of the numbers of languages, with longer
RTs in the bilingual lists (L1L2, L1L3) F(2,34) 8.20, p B0.01, and even longer
RTs in the trilingual list F(2,34) 4.10, pB0.05 (see Figure 4), without eliciting more
errors (F B1). Moreover, words in bilingual lists were processed faster than those in
the trilingual list F(2,34) 8.90, p B0.01.
For L2 words, the results follow exactly the same pattern: L2 target words were
processed faster in monolingual compared to bilingual F(2,34) 13.30, pB0.01 and
trilingual lists F(2,34) 9.8, p B0.01, but not significantly for errors. Comparison
between bilingual and trilingual lists show that L2 targets were processed faster
F(2,34) 6.71, p B0.01 in the bilingual lists.
Nevertheless, these patterns were not found for Spanish. We can observe
differences suggesting a slowdown of processing for L3 targets depending on the
list context, but the difference associated with this slowdown was not statistically
significant for both RTs and ERs.
Within-list language switching effects
In these analyses, we compared performance to words in the three languages (L1L3)
presented in multilingual lists as a function of the language of the word on the
directly preceding trial. ANAVOs were performed on the RT and percentage error
Figure 4. Mean RTs (ms) and SDs per language (L1, L2, L3) for pure and generalised lexical
decisions.
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International Journal of Multilingualism
13
data with target language (L1L3), language switch (switch vs. no-switch trials) and
list context (2 vs. 3 languages). Additional analyses compared performance on switch
trials as a function of the language of the word on the preceding trial.
In the RT analysis, there was a main effect of target language, F(2,34) 61.9, pB
0.001, with French words processed faster than English F(1,17) 49.5, pB0.001 and
Spanish words F(1,17) 74.43, pB0.001. There was also a significant difference
between L2 and L3, F(1,17) 44.1 pB0.001, with English words processed faster
than Spanish words. Moreover, there was a main effect of language switch, F(1,17)
16.31 p B0.001, with language repetition trials processed faster than language switch
trials. The interaction between these two factors was not significant (F B1),
nevertheless we developed paired comparison analysis to determine if this absence
of effect could be due to specific combination of languages.
For L1 targets, switch costs did not differ as a function of the language of the
preceding item on switch trials. In the lexical decision L1L2, the processing of L1
words in repetition (500 ms) was slowed down of 27.8 ms when they were preceded
by English words (527.8 ms). In L1L3 lexical decision we observed the same pattern
of results, with L1 words in repetition (509.4 ms) processed slower (22.1 ms) when
preceded by Spanish words (531.5 ms, cf. Table 3).
Here, the analysis of switch cost for L1 targets when preceded by L2 and L3
shows no significant differences (FB1). Interestingly, in the trilingual list, the switch
cost associated with L1 targets preceded by L2 was 10.9 ms, and 24.3 ms for L1
targets preceded by L3, with again no significant differences.
For English (L2) words, in the bilingual lists, the switch cost associated with L2
targets when preceded by L1 was 22.1 ms, and 32.8 ms when preceded by L3 words,
which was statistically significant F(1,17) 10.24, pB0.01. In the trilingual list, the
switch cost associated with L2 targets was also larger when preceded by L3 targets
(13.6 ms) than for those preceded by L1 targets (27.7 ms), which is also significant
F(1,17) 7.05, p B0.01.
Finally, for L3 targets, in the bilingual lists, the switch cost associated with L3
words was significantly larger F(1,17)17.56, pB0.001 when preceded by L2 (50.2
ms) than preceded by L1 (13.1 ms). In the trilingual list, we observed a reverse effect,
with a larger cost when preceded by L1 (76.1) compared to L2 (56.1), but the
difference was not significant (FB1).
Table 3. RTs (ms) for all languages in generalised lexical decision with two and three
languages, depending on the preceding trial.
Language switch
Lists
L1L2
L1L3
L2L3
L1L2L3
Language repetition
Preceding language
Targets L1
Targets L2
Targets L3
L1
L2
L1
L3
L2
L3
L1
L2
L3
527.8 (45.4)
531.5 (64.2)
529.8 (81.1)
543.2 (86.8)
606.5 (75.3)
567.7 (79.8)
561.1 (85.6)
602.4 (68,9.2)
641.5 (76.5)
650.7 (60.1)
679.4 (91.9)
659.4 (74.6)
500
584.4
509.4
628.4
534.9
600.5
518.9
588.8
603.3
(50.1)
(75.0)
(56.5)
(66.4)
(44.1)
(79.1)
(68.4)
(90.6)
(90.7)
14
X. Aparicio and J.-M. Lavaur
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Discussion
The aim of this experiment was to determine language switching effects depending on
the number of languages involved in the experimental list and the direction of the
switch. First, the monolingual lists (L1 L3) clearly show effects related to language
dominance, which are in line with previous findings of Aparicio et al. (2012) in a
trilingual study recording event-related potentials (ERP). Here, L1 words were
generally processed faster than L2 and L3 words, and L2 faster than L3, indicating
a hierarchy between the three languages which could be related to the AoA, and also to
the size of the different lexicons. This effect of language dominance persists in all the
multilingual lists (with two or three languages). It is important to notice that the
processing of any word (regardless of language) has been slowed down in the trilingual
list, certainly because of the multiplicity of language combinations increasing the
difficulty to perform the task. However, regardless of the condition, L1 (French) seems
to benefit from the highest level of activation, even if it suffers from the presence of
other languages in the list. This task requires the setting of greater mechanisms of
control and inhibition compare to pure or two-language lists. These results are fully
compatible with BIA-d model (Grainger et al., 2010), which predicts such modulations
in terms of activation of languages.
It is interesting to notice that the slowdown of processing due to the introduction
of other languages in a list concerns every language, with a variable intensity. This
could be related to the introduction of language switches (Grainger & Beauvillain,
1987). The slowdown is more important for all languages in the trilingual list,
indicating a progressive increase of language processing, related to the number of
languages to be processed. This could be explained by the numerous language
switches in the different directions when the three languages are involved.
Analyses on language switching effects revealed that the processing of languages
is affected by the language switch, but with really small effects for L1. In L1L2 lexical
decision, we found results similar to Experiment 1, with L1 words processed faster in
repetition (L1L1). Moreover, language switch is quite similar in L2L1 (27.8 ms)
direction compared to L1L2 (22.1 ms). Similar findings have been highlighted by
Grainger and Beauvillain (1987). These effects of switching could be related to
inhibitory control of lexical activation proposed in the BIA-d. The presentation of a
word in a given language leads to an overall inhibition of all the other languages.
Because inhibition needs to be overcome (Aparicio, Heidlmayr, & Isel, in press),
processing of following trials will be more difficult after a language switching
(Grainger & Beauvillain, 1987).
In L1L3 lexical decision, there is a clear asymmetry in language switching
direction. Language switching cost is more important in L1L3 direction compare to
L3L1 direction. The results highlighted in the L2L3 lexical decision also reflect these
effects, with a higher cost in L2L3 direction, indicating that the same mechanism of
inhibitory control is activated to control language activation. Results revealed that for
each lexical decision the dominant language (L1 or L2 depending on the decision) is
sensitive to repetition, which facilitates decision. Moreover, switch cost always seems
smaller when switching from the weakest language to the strongest one. This could be
due to the path followed to activate the lexical representation (lexical or conceptual,
Kroll & Stewart, 1994), or to a mechanism of inhibitory control of lexical activation.
Because L1 is automatic and strongly activated in unbalanced bilinguals (Meuter,
2005), it needs to be strongly inhibited, which could allow a more important cost
International Journal of Multilingualism
15
observed in this direction of switch, and confirmed with results in L3. Finally, the
results in the trilingual list highlight similar effects, i.e. language repetition effects
(more important in L1) and language switching effects, which seem less important
when switching from a non-dominant language to a dominant language.
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General discussion
In these experiments, we examined to what extent the language switch is influenced
by the degree of mastering of a given language, as well as the direction of language
switching. In other terms, we intend to determine if the access to lexical units relies
only on language context, or if the processes of access could be modulated by the
languages known by bilinguals and trilinguals. To reach these objectives, we choose
to compare the visual processing of words in several linguistic contexts (monolingual, bilingual, and trilingual). In both experiments, we observe differences
between the linguistic contexts, as well as language switching effects. On the whole,
the strength of the results is supported by several aspects of the research. Indeed, we
compared different language combinations (two or three languages in only one list),
with monolingual control condition (pure lists), in both bilinguals and trilinguals
participants. The number of participants recruited was appropriate to the study.
Experiment 1 was dedicated to replicate previous findings from Grainger and
Beauvillain (1987). In Experiment 2, the number of participants was limited given
that it was fairly difficult to recruit trilingual participants with similar AoA of L2
and L3. Nevertheless, the homogeneity of the participants allowed us to obtain
powerful data to support our hypothesis.
Altogether, the results obtained here support a language non-selective access to the
mental lexicon. Indeed, we obtain language dominance effects in both bilinguals
(Experiment 1) and trilinguals (Experiment 2). Languages seem to be organised within
the memory in a hierarchical mode, and the dominant language is easily activated
compared to other spoken languages. In addition, a non-dominant language (L2)
could be revealed as dominant upon a third language (L3), indicating the complexity
of the lexical connections among them. Interestingly, the effect of dominance remains
relevant even if participants have to deal with two or three languages simultaneously.
However, this effect is modulated by a slowdown of processing in mixed lexical
decisions. The asymmetries observed in languages are mainly due to AoA and
proficiency, indicating that the effect of dominance is not settled once for all and can
evolve depending on the skills of the participants in the three languages. Languages
are often learned at different life stages, not practised with the same frequency or in the
same context of usage; this fact is highlighted by an asymmetry between the languages
at a cognitive level (Kroll & Stewart, 1994; Meuter, 2005).
Moreover, we systematically observed effects due to language switching in
multilingual lists. It seems that language switching reflects, in a certain way, the
asymmetry observed among languages. If a switching effect is found in all switching
directions, the results indicate that the cost associated with switching is larger when
switching from a dominant language to a non-dominant language. This effect of
language switching could be explained in the light of BIA-d model (Grainger et al.,
2010), which postulates that lexical representations in the different languages are
interconnected by inhibitory links, and that the selection of the adequate lexical
candidate is made on the basis of the lexical units from all the languages known.
16
X. Aparicio and J.-M. Lavaur
We observed similar findings for language dominance and language switching
effects in both experiments, indicating that quantitative differences (in terms of
number of languages spoken) have a negative impact on the quality of processing. It
seems that recognition processes are slower in trilinguals compared to bilinguals in
the non-dominant languages, as suggested in Table 4.
Table 4. Comparison of RTs (ms) in bilinguals (Experiment 1) and trilinguals (Experiment 2)
in identical conditions of pure lexical decisions in L1 (French) and L2 (English), and
generalised lexical decisions (L1L2).
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Monolingual list
Bilinguals
Trilinguals
Bilingual list
L1
L2
L1
L2
491
497
527
561
527
534
585
628
This research also highlights the complexity of the links bounding languages inside
the mental lexicon, as well as the asymmetry among languages, mainly between L2
and L3, which has not been investigated so far. It is highly possible that the
importance of language switching depends on the temporal delay between the target
and the preceding trial. It seems that language switching elicits a higher cost when the
target word activates the language node presented in the dominant language, and this
activation requires an inhibition of the language node from the non-dominant
language previously activated. The asymmetry is based on the assumption that lexical
representations from L1 have a higher level of residual activation compared to L2 and
L3, due to its frequency of usage. Consequently, L1 words generate more bottom-up
activation to the L1 language node compared to L2 and L3 towards the corresponding
language node. Moreover, the cost associated with language switching is more
important between L2 and L3, because these two languages have a strong level of
asymmetry, indicated by a massive slowdown of processing.
Conclusion
To conclude, our data support the hypothesis of a multilingual lexicon integrated
within the memory, in which lexical representations of words are linked by inhibitory
connections. Lexical access appears to be supervised by formal aspects, but seems also
sensitive to the linguistic context related to the task. In early stages of processing, it
appears that trilinguals automatically activate the lexical representation of the three
languages, and the competition between the lexical candidates leads to language
switching costs, corroborating predictions from BIA-d model (Grainger et al., 2010).
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