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Bilingualism, Demographics, and Cognitive Control: A Within-Group Approach

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Previous studies have suggested a bilingual advantage in cognitive control as a result of the bilinguals’ language experience. However, the results are controversial as there are various factors (language proficiency, SES, culture, and intelligence, etc.) affecting cognitive control. In the current study, after between-group comparisons, we adopted a within-group approach by multiple regressions to investigate whether the performance by 10-to-75-year-old participants (N = 91) of tasks measuring inhibition, monitoring, and mental set shifting could be predicted by bilingualism, or demographic factors, or both. The results of multiple stepwise regression analyses showed that L2 proficiency was a significant predictor for conflict monitoring and inhibition, education and age were significant predictors for mental set shifting, and SES was a minor predictor for inhibition. These findings provide evidence that cognitive control is affected by both bilingualism and demographic factors. Future studies are encouraged to further identify the relationship between bilingualism and cognitive control from specific bilingual experience.
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ORIGINAL RESEARCH
published: 29 January 2020
doi: 10.3389/fpsyg.2020.00094
Edited by:
Sharlene D. Newman,
Indiana University Bloomington,
United States
Reviewed by:
Arturo Hernandez,
University of Houston, United States
Ramesh Kumar Mishra,
University of Hyderabad, India
Diane Poulin-Dubois,
Concordia University, Canada
*Correspondence:
Zhilong Xie
collinthank@163.com
Specialty section:
This article was submitted to
Cognition,
a section of the journal
Frontiers in Psychology
Received: 15 September 2019
Accepted: 14 January 2020
Published: 29 January 2020
Citation:
Xie Z and Zhou S (2020)
Bilingualism, Demographics,
and Cognitive Control:
A Within-Group Approach.
Front. Psychol. 11:94.
doi: 10.3389/fpsyg.2020.00094
Bilingualism, Demographics, and
Cognitive Control: A Within-Group
Approach
Zhilong Xie*and Shuya Zhou
Foreign Languages College, Jiangxi Normal University, Nanchang, China
Previous studies have suggested a bilingual advantage in cognitive control as a
result of the bilinguals’ language experience. However, the results are controversial
as there are various factors (language proficiency, SES, culture, and intelligence, etc.)
affecting cognitive control. In the current study, after between-group comparisons, we
adopted a within-group approach by multiple regressions to investigate whether the
performance by 10-to-75-year-old participants (N= 91) of tasks measuring inhibition,
monitoring, and mental set shifting could be predicted by bilingualism, or demographic
factors, or both. The results of multiple stepwise regression analyses showed that L2
proficiency was a significant predictor for conflict monitoring and inhibition, education
and age were significant predictors for mental set shifting, and SES was a minor
predictor for inhibition. These findings provide evidence that cognitive control is affected
by both bilingualism and demographic factors. Future studies are encouraged to
further identify the relationship between bilingualism and cognitive control from specific
bilingual experience.
Keywords: bilingualism, demographics, cognitive control, conflict monitoring, inhibition, mental set shifting
INTRODUCTION
Bilingualism is a common phenomenon, which includes both simultaneous bilinguals who learn
two languages simultaneously at early age, and sequential bilinguals who learn a second or
foreign language after the acquisition of the first language. The relationship between bilingualism
and cognition has been a topic of great concern. Previous research shows that bilinguals have
advantage over monolingual counterparts in cognitive control (Peal and Lambert, 1962;Bialystok
et al., 2004, 2009;Costa et al., 2009;Prior and Gollan, 2011). Cognitive control is a complex
mental process that individuals use to manage behaviors and thoughts, which is a composition of
multiple dimensions such as inhibition, mental set shifting, working memory updating, attention,
and conflict monitoring (Miyake et al., 2000;Bialystok et al., 2009;Green and Abutalebi, 2013;
Bialystok, 2017). Later research shows that bilingual advantage can also be reflected in neural
physiological studies in that bilinguals preserve higher efficiency in neural networks in terms
of the density/volume of gray or white matter compared to monolinguals, which is assumed
to delay cognitive aging (Gold et al., 2013;Abutalebi and Clahsen, 2014;Abutalebi et al., 2014;
Olsen et al., 2015). The bilingual advantage has been thought to come from inhibitory control
training in bilingual language use. It is reported that when bilinguals intend to use the target
language, the non-target language is also activated in the brain (Abutalebi and Green, 2007;Kroll
et al., 2008;Hoshino and Thierry, 2011), so in order to successfully use the target language, an
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Xie and Zhou Bilingualism, Demographics, and Cognitive Control
Inhibitory Control system (Green, 1998) is adopted to focus on
the target information and at the same time suppress the non-
target information. Thus, in such a long-term language control
experience, inhibitory control system becomes more efficient
and finally transfers to non-linguistic domain. Research indicates
that linguistic control and non-linguistic control activate similar
neural networks (Abutalebi and Green, 2007;Wu et al., 2019),
which suggests a common or shared neural mechanism for
language control and general cognitive control. If language
control activates a neural network that is responsible for general
cognitive control, it is reasonable to speculate that such language
control training may give rise to the enhancement of general
cognitive control abilities, i.e., bilingual advantage.
However, there is a contentious debate on the bilingual
advantage. Quite a few studies did not find evidence. Hilchey and
Klein (2011)s seminal review compared previous studies on the
Simon effect/flanker interference to examine inhibitory control
between bilinguals and monolinguals. Their conclusion indicates
little or no bilingual advantage among children and young adult
groups, whereas it is robust in the middle-aged and old-aged
participants and it is more obvious in global RT advantage,
suggesting better conflict monitoring, but not inhibitory control.
After their review, more studies have questioned the existence
of bilingual advantage. Paap and Greenberg (2013) conducted
three studies to compare a large sample of young adult bilinguals
(n= 122) and monolinguals (n= 151) on the bilingual
advantage regarding 15 indicators of cognitive control. Multiple
tasks including Antisaccade (Study 1), Simon (Studies 1–3),
flanker (Study 3), and color-shape switching (Studies 1–3) were
administered to measure inhibition, conflict monitoring, and
mental set shifting. However, the results showed no bilingual
advantage on any indicator measured in the above tasks, and
there was no consistency between different measuring tasks.
After Paap and Greenberg’s study, the number of papers
challenging the bilingual advantage increased notably. Quite
a few scholars have doubted the significance and validity of
the current bilingual advantage research and have claimed
that bilingual advantages may not exist or are restricted to
specific circumstances (Anton et al., 2014;Gathercole et al.,
2014;Paap et al., 2015;Sanchez-Azanza et al., 2017;Donnelly
et al., 2019). Some meta-analyses reviewed previous studies
on bilingual advantage but reported mixed results. Lehtonen
et al. (2018) compared bilinguals’ and monolinguals’ performance
in six cognitive control dimensions by using effect sizes
from 152 previous studies on adults. They concluded that
their analyses revealed only a small bilingual advantage in
dimensions of inhibition, shifting, and working memory, but
no bilingual advantage in monitoring or attention. Furthermore,
after correcting estimates for observed publication bias, they
found no evidence for a bilingual advantage at all. However,
van den Noort et al. (2019)s findings are contradictory. They
searched the Medline, ScienceDirect, Scopus, and ERIC databases
for all original data and reviewed studies on bilingualism and
cognitive control, with a cut-off date of October 31, 2018. After
the meta-analyses, they found that the majority, 54.3%, reported
beneficial effects of bilingualism on cognitive control tasks, 28.3%
mixed results, and 17.4% against its existence. These inconsistent
findings have led to some doubts about the veracity of bilingual
advantage and thus the current debate in the field (Antoniou,
2019;de Bruin, 2019;Paap, 2019).
How to interpret the contradictory findings? A range of
factors are thought to account for the inconsistent results.
Firstly, some scholars claimed that the field suffers from
publication bias, which suggested that studies supporting the
bilingual advantage hypothesis were most likely to be published,
whereas the ones challenging it were less likely to be published
(de Bruin et al., 2015).
Secondly, cognitive control has been reported to be modulated
by participant relevant variables, including age (Tao et al., 2011),
socio-economic status – SES (Morton and Harper, 2007), culture
(Yang et al., 2011), intelligence (Xie and Pisano, 2019), and
immigration status (Kousaie and Phillips, 2012). Specifically,
young adult participants have been reported to perform much
better than children and older adults because they are in the
peak development of cognitive control, and bilingual advantages
are more robust among older adult bilinguals as their cognitive
control is in decline (Bialystok et al., 2009). Participants with
higher SES tend to have better cognitive control abilities (Calvo
and Bialystok, 2014), and better cognitive control is linked to
higher scores on intelligence tests (Xie and Pisano, 2019).
Thirdly, benefits from bilingualism are inconsistent because
individuals vary in the number and types of experiences they
have that promote superior cognitive control. It has been argued
that the variability in the language context of bilingual speakers
(or variability of bilingual experience) may modulate cognitive
control in different contexts (Green and Abutalebi, 2013).
For example, bilinguals who have more practice of switching
languages may be superior in mental set shifting compared
to monolinguals or bilinguals who do not have such practice
(Prior and Gollan, 2011;Yudes et al., 2011). Bilinguals with
higher L2 proficiency or more practice of L2 speaking training
may have better ability in conflict monitoring (Xie and Dong,
2017;Xie and Pisano, 2019). Bilinguals may also show better
conflict monitoring in high demanding version of the flanker
task (Costa et al., 2009). To sum up, it has been suggested that
the mixed results of bilingual advantage could have come from
multiple variables: particularly, the varying demographic features
of the bilingual participants, and the individual differences of
bilingual experience.
Although previous studies have assessed different factors
affecting cognitive control, most of them relied on quasi-
experimental designs where bilinguals were compared to
monolinguals (or compared to different bilingual groups). Such
designs are fruitful in providing evidence of bilingual advantage,
but this kind of design more or less entails the randomization
of participants into the different groups. Thus, it is difficult
to exclude the role of these confounding factors, which may
co-vary with relevant variables. One way to avoid such between-
group confounding effects is to conduct longitudinal research.
For example, Crivello et al. (2016) examined whether growth
in bilingualism (indicated by increased number of translation
equivalents) improves cognitive control over a period of 7-
month time. Bilingual children were measured on expressive
vocabulary and translation equivalents and on a battery of
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cognitive control tasks (conflict, delay, and working memory)
when they were 24 and 31 months of age. It was found that within
the bilingual participants, increase of the number of translation
equivalents, rather than vocabulary growth, predicted the better
performance on conflict tasks but not on delay tasks. This
within-group design confirmed the relation between bilingualism
and cognitive control. Another way to avoid bilingual and
monolingual comparison consists in examining the impact
of the bilingual experiences within bilingual participants. For
example, Soveri et al. (2011) used multiple regression to study
whether the performance of 30- to 75-year-old Finnish–Swedish
bilinguals (N= 38) on cognitive control tasks (inhibition,
updating, and mental set shifting) could be predicted by language
switching experience, L2 age of acquisition, or by the language
proficiency. The results showed that a higher rate of everyday
language switches was related to a smaller mixing cost in errors,
which reflected top-down management of competing task sets,
resembling the bilingual situation where decision of which
language to use has to be made in certain language context. In a
more recent example, DeLuca et al. (2019b) investigated whether
differences in bilingual experiences could confer systematic
brain adaptations among 65 healthy right-handed bilinguals
(mean age: 31.7, range: 18–52). Correlation and regression
models revealed that L2 AoA was found to significantly predict
expansions in the left nucleus accumbens and the bilateral
thalamus. Specifically, length of L2 immersion significantly
predicted significant adaptations in posterior sections of the right
caudate nucleus; years of active L2 use predicted an expansion
in the left nucleus accumbens, and active L2 immersion
predicted both an expansion and contractions in the right
caudate nucleus. Briefly, specific experience-based factors related
to bilingualism (such as extent and duration of active L2
use) predicted specific adaptations in the brain. This study
sets an example of investigating how different dimensions of
bilingualism may affect brain structures and functions within
bilinguals (DeLuca et al., 2019a).
Following this line of research, the current study intends to
investigate the relationship between bilingualism and cognitive
control by introducing a similar within-group approach. We
employ multiple regressions to investigate whether participants’
performance on tasks measuring three aspects of cognitive
control (inhibition, conflict monitoring, and mental set shifting)
could be predicted by either bilingualism itself or participant
relevant factors (such as SES, age, and IQ), or both. We
hypothesize that both factors may be significant predictors of
cognitive control but in different dimensions.
MATERIALS AND METHODS
Participants
The current study included 91 healthy, right-handed English,
Chinese monolinguals and Chinese-English bilinguals between
10 and 75 years of age (M= 26.45). The English monolinguals
(n= 26, limited L2 s: Spanish, Chinese, and French) were
participants from New York City and the suburban area. The
Chinese monolinguals (n= 31, limited L2: English) and the
Chinese-English bilinguals (n= 34) were participants from
the Jiangxi Province of China and Jiangxi Normal University,
respectively. All participants voluntarily participated in the study
and gave informed consent, and their rights were protected in
accord with the ethical standards of the Academic Committee of
Jiangxi Normal University.
On the average, they were quite highly educated
(M= 14.02 years). All the monolinguals had very limited
L2 proficiency. The English monolinguals had a mean of 4.62
(out of 40) for L2 proficiency. The Chinese monolinguals had a
mean of 7.06 for L2 proficiency. Therefore, although they were
considered as monolinguals in the current study, they could also
be classified as bilinguals with a relatively low L2 proficiency.
All the bilinguals were Chinese native speakers who formally
learnt English as a foreign language at around age 10 in school
(Mean of L2 proficiency = 23.38). In order to obtain participants’
demographic information and their language proficiency, we
adopted the language experience and proficiency questionnaire
(Marian et al., 2007). Such questionnaires are widely used in
bilingual research, and are significantly correlated with objective
measures of language proficiency (Marian et al., 2007;Prior
and Gollan, 2011). In the language proficiency questionnaire,
language skills were composed of listening, speaking, reading,
and writing, respectively in L1 and L2 on a scale from 0 to 10,
where 0 corresponded to no skills in that particular language and
10 to skills at a native level. There was a significant difference
between their L1 and L2 language proficiency (33.70 vs. 12.46),
t= 19.598, p<0.001, and all the groups differed in L2 proficiency
(ps<0.05, see Table 1).
Furthermore, we adopted Ravens Matrices (Raven et al., 1977;
Li, 1989) to measure participants’ IQ and used participants
parental education as proxy of SES1(Wermelinger et al., 2017).
The results showed no significant group differences in IQ (F<1,
p= 0.569), but significant group differences in SES. English
monolinguals had a significant higher level of SES compared to
the other two similar groups (p= 0.020). Moreover, the three
1We recognize that a more objective indicator of SES should include family
income, but because our participants did not provide income data and the Chinese-
English bilinguals were still college students without income from any profession,
we followed Wermelinger et al. (2017) and used all participants’ parental education
as an approximate indicator of SES.
TABLE 1 | Demographic scores of all participants (N= 91).
English Chinese Chinese-English Total
Monolinguals Monolinguals Bilinguals M (SD)
(n= 26) (n= 31) (n= 34) (n= 91)
Age (years) 37.65b(19.21) 21.55a(3.56) 22.35a(1.86) 26.45 (12.60)
Education 14.21b(3.95) 11.29a(2.51) 16.35c(1.86) 14.02 (3.51)
(years)
SES (1–7) 3.69b(1.34) 2.68a(1.58) 2.69a(1.58) 2.97 (1.57)
IQ (0–72) 63.58 (5.16) 65.00 (5.59) 64.79 (5.34) 64.52 (5.35)
L1 Proficiency* 34.31 (5.68) 31.62 (2.62) 35.15 (1.78) 33.70 (3.85)
L2 Proficiency* 4.62a(5.85) 7.06b(2.87) 23.38c(4.37) 12.46 (9.59)
*Total scores of language proficiency = 40 (listening +speaking +reading +
writing). Means in the same row with different superscript letters differ from each
other significantly at p <0.01.
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groups also differed in age, with the English monolinguals much
older than the other two (see Table 1).
Cognitive Control Tasks
In the current study, we employed two cognitive control tasks to
measure three dimensions: inhibition, conflict monitoring, and
mental set shifting.
The Flanker Task
The flanker task (Eriksen and Eriksen, 1974) has been widely used
to measure cognitive control, of which inhibition and conflict
monitoring are two main components. Inhibition indicates the
ability to suppress responses that are inappropriate in a given
situation (Luk et al., 2010;Paap and Greenberg, 2013), indicated
by the RT differences between incongruent trials and congruent
trials, which is a long established measure in the study of bilingual
advantage. Conflict monitoring indicates the ability to monitor
one’s performance or internal state, or monitor the context and
evaluate whether conflict resolution processes should be involved
when the target information is presented (Costa et al., 2009;
Paap and Greenberg, 2013). This was first proposed by Bialystok
et al. (2004), who suggested that the bilingual advantage (of faster
speed) both for congruent trials and incongruent trials on the
Simon task may reflect “the ability to manage attention to a
complex set of rapidly changing task demands”(p. 292). Costa
et al. (2009) adopted a flanker task and put forward that “the
bilingual advantage in overall RTs may reveal the better ability
of bilinguals to handle tasks that involve mixing trials of different
types: bilinguals would be more efficient at going back and forth
between trials that require implementing conflict resolution and
those that are free of conflict” (p. 136). Managing two languages
may enhance conflict monitoring because “the bilinguals need
to continuously monitor the appropriate language for each
communicative interaction. That is, proper communication in
bilingual settings involves the monitoring of the language to
be used depending on the interlocutor(s) language knowledge”
(p. 136). The indicator for conflict monitoring is sometimes the
RT difference between trials in a pure block and the congruent
trials in a block where congruent and incongruent trials are
mixed, sometimes RT on the congruent trials, or RT on both the
congruent and incongruent trials (Bialystok et al., 2004;Costa
et al., 2009;Paap and Greenberg, 2013). In the current study,
we use the RTs on each condition as the indicator of conflict
monitoring (as in Dong and Xie, 2014;Xie and Dong, 2017).
In the current flanker task, there were three conditions:
congruent, incongruent, and neutral. In the congruent condition,
the target chevron (in red color) was flanked by black chevrons
pointing to the same direction, thus creating facilitation. In
the incongruent condition, the target chevron was flanked by
black chevrons pointing to the opposite direction, thus creating
conflict. In the neutral condition, the target chevron was flanked
by black diamond symbols that share no shape similarity, thus
creating no conflict or facilitation.
The flanker task, adapted from previous studies (Luk et al.,
2010;Xie and Dong, 2017), was computerized via E-prime 2.0.
The task was composed of a practice block with feedback (smiling
face for correct, frowning face for incorrect) and a formal
experimental block without feedback. In each trial, there was a
fixation stimulus of “ +” for 250 ms. Then each condition of the
stimulus appeared randomly for 2000 ms. After that, participants
were required to press the designed button corresponding to the
direction of each target red chevron. A new trial would start
again after the participant’s response or 2000 ms. One thing to
note is that in the task, each participant would not begin the
formal experiment until he or she performed with an accuracy
rate above 80% in the practice block, which was to ensure focused
attention on the task. There were altogether 108 trials in the
experimental block.
The Wisconsin Card Sorting Test (WCST)
One of the most widely used tasks to measure mental set shifting
is the Wisconsin Card Sorting Test (Barceló and Knight, 2002;
Moriguchi and Hiraki, 2009;Nyhus and Barcelo, 2009). Mental
set shifting is the ability to shift back and forth between multiple
tasks, operations, or mental sets (Monsell, 1996;Miyake et al.,
2000). In this test, based on four stimulus cards that included one
red triangle, two green stars, three yellow crosses, and four blue
circles, participants were required to classify the response card,
which was a constellation of these numbers, colors, and shapes.
Participants were presented with feedback of correctness after
each response, and based on the feedback they could deduce new
implied rules to classify the next trial. What was unknown to the
participants was that the implied rule would change after a few
trials (varied from 5–9 trials).
The computerized version of WCST programed in E-prime
2.0, which followed previous studies (Yudes et al., 2011;Dong
and Xie, 2014;Xie and Pisano, 2019), was composed of 12
practice trials and 128 formal experimental trials. Each trial began
with a fixation “ +” for 1000 ms. After that the four stimulus
cards appeared in the upper half of the screen while a response
card appeared at the same time in the lower half of the screen.
Participants were required as soon as possible to sort out the
response card according to any of the stimulus cards by pressing
designated buttons. Then a feedback appeared for 1000 ms before
the next trial. In performing the task, there was an optional
break in the middle.
Statistical Analyses
To provide a comprehensive result, we first conducted a repeated
measures analyses with condition as within-group variable
and group as between-group variable, and then we conducted
multiple linear step-wise regression analyses separately for
each task, with the processing response times (RTs) (conflict
monitoring) and the flanker effect (inhibition) in the flanker task,
the overall performance of completed categories and errors in
the WCST (mental set shifting) as dependent variables, and with
L1 proficiency, L2 proficiency, SES, age, education, and IQ as
independent variables.
RESULTS
For the flanker task, we calculated correct response times,
excluding errors and correct responses that fell three standard
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TABLE 2 | Flanker task performance across groups (N= 91).
English Chinese Chinese-English
Monolinguals Monolinguals Bilinguals
(n= 26) (n= 31) (n= 34)
M(SD) M(SD) M(SD)
Congruent condition 600.4b(118.9)534.5a(105.4)522.8a(78.8)
Neutral condition 619.5b(115.6)553.4a(89.1)548.5a(91.6)
Incongruent condition 642.3(112.7)593.6(86.8)591.0(85.0)
Flanker effect 41.9(50.5)59.1(40.3)68.2(49.5)
Means in the same row with different superscript letters differ from each other
significantly at p <0.05.
deviations outside the mean time for each subject in each
condition, which occupied for 2.52% of the total data. For the
WCST, we calculated overall RTs, completed categories, overall
errors, and types of errors independently.
Flanker Task
In the flanker task, as mentioned above two indices were
calculated to assess participants’ performances (Bialystok et al.,
2004;Costa et al., 2009;Paap and Greenberg, 2013). The first one
is flanker effect, which is the response-time difference between
incongruent trials and congruent trials. The flanker effect has
been considered as an indicator of inhibition. Smaller flanker
effect indicates better ability of inhibition (inhibitory control).
The second one is response times in each condition, which is
considered as an indicator of conflict monitoring, reflecting an
ability to monitor a context where conflict occurs or not. Faster
RTs indicate better ability of conflict monitoring. Data of all
participants’ performances are presented in Table 2.
Repeated measures analyses with condition as within-group
variable and group as between-group variable were conducted
to examine whether there were differences across conditions
and across groups. Results of within-subjects effects revealed a
significant effect of condition, F(2,176) = 72.035, p<0.001,
η2= 0.450, but no significant condition and group interaction,
F(4,176) = 1.460, p= 0.216, η2= 0.032. Planned comparisons
showed that all participants responded more quickly in the
congruent condition (548.94 ms) than in the neutral (570.44 ms),
F(1,90) = 19.665, p<0.001, η2= 0.179, and the incongruent
conditions (606.53 ms), F(1,90) = 133.277, p<0.001, η2= 0.597.
Participants also responded more quickly in the neutral condition
(570.44 ms) than in the incongruent condition (606.53 ms),
F(1,90) = 68.389, p<0.001, η2= 0.432.
Results of between-subjects effects showed that there
were significant differences between groups, F(2,88) = 4.262,
p= 0.017,η2= 0.088. ANOVA analyses results showed significant
group differences on the congruent condition (p= 0.010) and
the neutral condition (p= 0.013) but not on the incongruent
condition or on the flanker effect (ps>0.05). Results of
post hoc bonferroni multiple comparisons showed significant
differences between the English monolinguals and the Chinese
monolinguals on congruent condition and neutral condition
(p= 0.047, p= 0.040, respectively), between the English
monolinguals and the Chinese-English bilinguals on congruent
and neutral conditions (p= 0.012, p= 0.020, respectively), but
not between the Chinese monolinguals and the Chinese-English
bilinguals (ps>0.05) (see Figure 1).
However, besides different L2 proficiency across groups,
demographic variables such as age, SES, and education were also
different across the three groups (ps<0.05, see Table 1), so we
could not tell what was the real factor(s) for the differences on the
flanker task performance. Apparently, the English monolinguals
were much older (M= 37.65) than the other groups (M= 21.55,
22.35, respectively), although they had higher SES (M= 3.69)
compared to the other two groups (M= 2.68, 2.69, respectively).
These results may be caused by confounding factors and thus
need further analyses.
Therefore, in order to find out what variables may predict
the performance of the flanker task, we conducted step-wise
multiple regression analyses with RTs of each condition and the
flanker effect as dependent variables, with L1 proficiency, L2
proficiency, SES, age, education, and IQ as independent variables.
The results of multiple regressions on the flanker congruent
condition showed that only L2 proficiency remained in the
model in predicting the RTs of congruent condition, R= 0.297,
R2= 0.088, adjusted R2= 0.078, F(1,89) = 8.591, p= 0.004. Other
variables such as age, education, SES, IQ, and L1 proficiency were
excluded from the model (Table 3).
The results of multiple regressions on the flanker neutral
condition similarly showed that only L2 proficiency significantly
predicted the RTs of neutral condition, R= 0.250, R2= 0.063,
adjusted R2= 0.052, F(1,89) = 5.955, p= 0.017. Other variables
such as age, education, SES, IQ, and L1 proficiency were excluded
from the model (Table 3).
However, the results of multiple regressions on the flanker
incongruent condition showed that only education significantly
predicted the RTs of incongruent condition, R= 0.299, R2= 0.089,
adjusted R2= 0.079, F(1,89) = 8.708, p= 0.004. Other variables
such as age, SES, IQ, L1 proficiency, and L2 proficiency were
excluded from the model (Table 3).
In addition, we conducted multiple regression analyses on the
flanker effect, which is an indicator of inhibition. The results
of multiple regressions on the flanker effect showed that both
SES and L2 proficiency significantly predicted the flanker effect,
R= 0.317, R2= 0.100, adjusted R2= 0.080, F(1,89) = 4.906,
p= 0.010. Other variables such as age, IQ, and L1 proficiency were
excluded from the model (Table 3).
To summarize, the overall results of the multiple regression
analyses of the flanker task showed that L2 proficiency predicted
the congruent condition RTs and the neutral condition RTs,
education predicted the incongruent condition RTs, and SES and
L2 proficiency predicted the flanker effect. As mentioned above,
RTs reflect the ability of conflict monitoring and flanker effect
reflects the ability of inhibition, so we can generally conclude
that L2 proficiency was a major predictor of conflict monitoring
whereas education was a minor. Furthermore, both SES and L2
proficiency significantly predicted inhibition.
WCST
In the WCST, we calculated five indices to reflect mental set
shifting. The first one is overall response times, which reflected
participants’ speed during the task. The second one is the total
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Xie and Zhou Bilingualism, Demographics, and Cognitive Control
FIGURE 1 | Flanker task.1pc performance across groups and conditions.
TABLE 3 | Results of the multiple regressions for the flanker task performance.
Predictors UC* SC* Dependent variable tSig.
BStd. error Beta
L2 proficiency 3.244 1.107 0.297 Congruent RTs 2.931 0.004
L2 proficiency 2.662 1.091 0.250 Neutral RTs 2.440 0.017
Education 8.169 2.768 0.299 Incongruent RTs 2.951 0.004
SES 6.734 3.086 0.221 Flanker effect 2.182 0.032
L2 proficiency 1.033 0.503 0.208 2.052 0.043
*UC= unstandardized coefficients; SC= standardized coefficients.
number of correct categories participants completed. The third
one is the total number of errors participants made. The fourth
one is the total number of perseverative errors that participants
failed to change to a correct mental rule after receiving negative
feedback. The fifth one is the total number of previous category
errors that participants continued in sorting cards according to
the previous category dimension despite the negative feedback.
Data of all groups’ performances are presented in Table 4.
ANOVA analyses results showed that there were no RT
differences across the groups (p>0.05). However, there
were significant group differences on completed category
F(2,90) = 10.975, p<0.001, overall errors F(2,90) = 24.149,
p<0.001, perseverative errors F(2,90) = 26.027, p<0.001, and
previous category errors F(2,90) = 34.287, p<0.001. Post hoc
bonferroni multiple comparisons showed that both the English
monolinguals and the Chinese-English bilinguals completed
more categories than the Chinese monolinguals (p= 0.002,
p<0.001, respectively). The English monolinguals produced
fewer overall errors and perseverative errors than the Chinese-
English bilinguals (p= 0.046, p= 0.029), and the Chinese-English
TABLE 4 | WCST performance across groups (N= 91).
English Chinese Chinese-English
Monolinguals monolinguals bilinguals
(n= 26) (n= 31) (n= 34)
M(SD) M(SD) M(SD)
WCST RTs 1693.7(602.5)1383.7(549.7)1549.1(521.0)
Completed category 8.9b(3.7)5.9a(2.7)9.5b(3.4)
Overall errors 46.8a(17.2)73.2c(13.4)56.3b(13.5)
Perseverative errors 25.2a(17.7)54.4c(15.4)35.9b(13.8)
Previous category errors 12.7a(12.9)40.5b(17.6)18.0a(9.7)
Means in the same row with different superscript letters differ from each other
significantly at p <0.05.
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Xie and Zhou Bilingualism, Demographics, and Cognitive Control
bilinguals produced fewer errors than the Chinese monolinguals
(ps<0.001). Finally, the English monolinguals and the Chinese-
English bilinguals produced similar previous category errors but
both were better than the Chinese monolinguals (ps<0.001).
These mixed results are actually complicated. As we have
mentioned earlier in the flanker task performance, the three
groups differed in L2 proficiency and in demographic factors such
as age, SES, and education, so it is difficult to speculate which
factor or a combination of the factors might have contributed to
the differences.
Therefore, similar to the flanker task, in order to find out what
variables contributed to the performance of the WCST task, we
conducted step-wise multiple regression analyses with each index
as a dependent variable, whereas L1 proficiency, L2 proficiency,
SES, age, education, and IQ as independent variables. The results
of multiple regressions on the overall RTs showed that age was
the only predictor for the overall RTs of the WCST, R= 0.357,
R2= 0.127, adjusted R2= 0.117, F(1,89) = 12.965, p= 0.001 (see
Table 5). Other variables such as L2 proficiency, education, SES,
IQ, and L1 proficiency were excluded from the model (ps>0.05).
The results of multiple regressions on the number of
completed categories showed that education was the only
factor that remained in the model in predicting the completed
categories of the WCST, R= 0.396, R2= 0.157, adjusted
R2= 0.147, F(1,89) = 16.548, p<0.001 (see Table 5). Other
variables such as L2 proficiency, age, SES, IQ, and L1 proficiency
were excluded from the model (ps>0.05).
The results of multiple regressions on overall errors,
perseverative errors, and previous category errors showed that
both education and age were significant predictors (see Table 5):
overall errors, R= 0.456, R2= 0.207, adjusted R2= 0.189,
F(2,88) = 11.520, p<0.001; the perseverative errors, R= 0.477,
R2= 0.227, adjusted R2= 0.210, F(2,88) = 12.808, p<0.001;
the previous category errors, R= 0.498, R2= 0.248, adjusted
R2= 0.231, F(2,88) = 14.370, p<0.001. Other variables such as
L2 proficiency, SES, IQ, and L1 proficiency were excluded from
the model (ps>0.05).
To summarize, the overall results of the multiple regression
analyses of the WCST showed that age and education mainly
predicted the overall performance of the task. There are subtle
differences, though, in that age was the only predictor for the RTs,
education was the only predictor for the completed categories,
whereas both education and age significantly predicted the
overall errors and different types of errors. Therefore, in all, we
could presumably conclude that age and education are the main
factors for mental set shifting.
DISCUSSION
Given the controversial results of bilingual advantage in
cognitive control, the current study set out to explore this
issue with a within-group approach where the relationship
between multiple factors including bilingualism and cognitive
control was investigated. In a sample of 91 participants
including English monolinguals, Chinese monolinguals, and
Chinese-English bilinguals, we found that L2 proficiency was
a significant predictor for cognitive control, particularly in
conflict monitoring and inhibition but not in mental set shifting.
Broadly speaking, this result provides at least partial support
for the hypothesis that the bilingual advantage is related to
bilingual experience that requires cognitive control (Green, 1998;
Abutalebi and Green, 2007;Bialystok et al., 2009;Costa et al.,
2009;Hartanto and Yang, 2019).
The results that bilingualism (indicated by L2 proficiency)
is related to inhibition and conflict monitoring (as tested by
the flanker task) are consistent with some previous studies. For
example, Bialystok and Martin (2004) showed that bilingual
children outperformed monolinguals in dimensional card change
sorting task. This better inhibitory control reflects the ability
of ignoring perceptual information. In another study Bialystok
et al. (2008) used a spatial Stroop task to compare the different
performances between elderly bilinguals and monolinguals. They
demonstrated that bilinguals outperformed monolinguals on
the interference effect (inhibition). According to Hilchey and
Klein (2011), the bilingual advantage on inhibition is sporadic.
However, the result of the current study showed that bilingualism
(L2 proficiency) is indeed a significant predictor of inhibition.
The relation between bilingualism and conflict monitoring
is robust in the current study. L2 proficiency significantly
predicted the flanker task performance in both congruent
and neutral trials (but no effect for incongruent trials). This
TABLE 5 | Results of the multiple regressions for WCST.
Predictors UC* SC* Dependent variable t Sig.
BStd. error Beta
Age 16.050 4.457 0.357 RTs 3.601 0.001
Education 0.410 0.101 0.396 Completed category 4.068 0.000
Education 1.455 0.513 0.284 Overall errors 2.839 0.006
Age 0.397 0.143 0.278 2.784 0.007
Education 1.617 0.551 0.314 Perseverative errors 3.163 0.002
Age 0.426 0.153 0.273 2.751 0.007
Education 0.378 0.508 0.357 Previous category errors 3.859 0.000
Age 0.227 0.141 0.232 2.313 0.023
*UC, unstandardized coefficients; SC, standardized coefficients.
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Xie and Zhou Bilingualism, Demographics, and Cognitive Control
finding is partly consistent with a few studies. For example, in
Bialystok et al. (2004), bilinguals showed faster response times
(monitoring) compared to monolinguals, both in congruent trials
and incongruent trials of a Simon task. In Emmorey et al. (2008),
a flanker task was adopted to compare the performances between
middle-aged bilinguals and monolinguals that were matched
on SES. Their results showed that the bilingual participants
responded more rapidly on congruent trials and incongruent
trials than did the monolinguals, which is partially in conformity
with the current finding. Similarly, Costa et al. (2009) examined
whether there were different performances between young adult
monolinguals and bilinguals in the flanker task under different
cognitive demands, and they found that the bilinguals were faster
in performing the task when it is under high cognitive demand
(by varying the percentage of congruent and incongruent trials).
In a more recent study by Xie (2018), it was shown that
among the three bilingual groups varying in L2 proficiency,
the high L2 proficiency bilingual group performed faster than
the low L2 proficiency bilingual group in congruent, neutral,
and incongruent trials, which further proves that bilingualism is
significantly related to response times, which presumably reflects
conflict monitoring.
However, the regression analyses results of the current study
showed no relation between bilingualism and mental set shifting.
This result may be related to the fact that our participants
did not have enough language switching experience. For the
monolinguals in our study, they surely did not have such language
switching experiences. Even for the Chinese-English bilinguals,
they had few opportunities of speaking English. In mainland
China, English is taken as a foreign language, so students
usually do not have the environment and necessity of speaking
English in their daily life, let alone the experience of language
switching. Costa et al. (2009) suggested that bilinguals who
do not have switching experience may show an advantage in
conflict monitoring. On the contrary, studies show that even
short-term language switching training can transfer to non-
linguistic domain for the mental set shifting among bilinguals
(Timmer et al., 2019). This assumed relation between language
switching and mental set shifting has support from neuro-
imaging studies. For example, studies have shown that different
neural networks are activated when different dimensions of
cognitive control are required in language use. It is shown that the
middle frontal gyrus and left parietal lobe are more active when
bilinguals switch between languages or non-linguistic tasks (Sun
et al., 2019). This experience-dependent neural effects are in fact
consistent with a newly proposed theory – neuroemergentism,
which states that the effects of bilingualism on cognitive control
is a combination of much smaller systems that are sensitive to
age, age of acquisition, proficiency or performance level, specific
language experience, and individual difference. The effects are
developmental, dynamic, and non-linear, and are likely the
products of different forms of bilingual experiences. Thus it is
suggested that future research of the bilingual advantage should
not center on whether language experience affects cognitive
control or not, but on how language experience at different
points in life dynamically affects cognitive control (Li et al., 2014;
Hernandez et al., 2018, 2019).
Moreover, the current study found that some demographic
factors were significantly associated with cognitive control in
some dimensions. Specifically, age and education were associated
with mental set shifting, whereas SES associated with inhibition,
which conflicts with some recent studies in that SES is related
to conflict monitoring (reflected by response times) (e.g., Naeem
et al., 2018;Xie and Pisano, 2019). Nevertheless, these results
are generally in line with the findings that higher education
and SES are correlated positively with cognitive control, whereas
age is positively correlated with cognitive control for children
and young adult participants but negatively correlated with
cognitive control for older adults (Valian, 2015;van den Noort
et al., 2019;Xie and Pisano, 2019). In the current study,
however, we did not find association between cognitive control
and intelligence. In Xie and Pisano (2019), intelligence was
reported a significant predictor of congruent trials in the flanker
task. In Woumans et al. (2016), a longitudinal study was
carried out to examine whether immersion bilingual schooling
could improve cognitive control. Their results found that
the children attending bilingual kindergarten improved not
only in cognitive control but also in intelligence. All these
results provide evidence that demographic factors do really
affect cognitive control, although why and how demographic
factors (such as age, education and SES) are related to one
dimension but not other remains unknown, which calls for future
research to identify how each demographic factor is related
to specific dimension of cognitive control under what specific
bilingual context.
CONCLUSION
In the current study, we used a within-group approach
to investigate multiple factors that may potentially affect
cognitive control. The results showed that both bilingualism
and demographics contributed to cognitive control. Our study
presents a complementary methodological approach that will
hopefully shed more light on the important issue of the
bilingual advantage. It is without doubt that the measurement
of the various aspects of bilingual experience, the multiple
factors in demographics, and the identification of various
dimensions of cognitive control are to be further clarified
in future studies.
DATA AVAILABILITY STATEMENT
The datasets generated for this study are available on request to
the corresponding author.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by the Academic Committee of Jiangxi Normal
University. Written informed consent to participate in this study
was provided by the participants’ legal guardian/next of kin.
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Xie and Zhou Bilingualism, Demographics, and Cognitive Control
AUTHOR CONTRIBUTIONS
All authors listed have made a substantial, direct and intellectual
contribution to the work, and approved it for publication.
FUNDING
This research was supported by grants from the National Social
Science Fund of China (19BYY083) to the corresponding author.
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Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Copyright © 2020 Xie and Zhou. This is an open-access article distributed under the
terms of the Creative Commons Attribution License (CC BY). The use, distribution
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Frontiers in Psychology | www.frontiersin.org 10 January 2020 | Volume 11 | Article 94
... For instance, Xie and Zhou (2020) investigated whether the performance by 10-to 75year-old participants (N = 91) of tasks measuring cognitive control could be predicted by bilingualism, demographic factors, or both. The findings revealed that second language (L2) proficiency was a significant predictor for conflict monitoring and inhibitory Introduction 4 control. ...
... components: response inhibition and interference suppression(Rey-Mermet et al., 2018).Moreover, some researchers suggested that individual differences or methodological factors affect the bilingual effect in cognitive control research(Arizmendi et al., 2018;van den Noort et al., 2019;von Bastian et al., 2016;Xie & Zhou, 2020). Hence, this review also provides an overview of individual differences and methodological factors that might influence, especially in inhibitory control ability.The discussion section structure is based on the three research questions outlined at the end of chapter two. ...
Thesis
Background: For many years, research has focused on the cognitive consequences of bilingualism. While earlier studies reported that bilinguals were more efficient in executive control, particularly with respect to inhibitory processes (bilingual advantage), more recent studies have often failed to replicate this effect. Moreover, studies have shown the unity and diversity of inhibitory control and distinguished between response inhibition and interference suppression. Aim: This literature review aims to elucidate whether the bilingual inhibitory control advantage, especially in its two components, exists across the life span and to investigate its modulating factors. Method: A literature search was conducted via EBSCO in many databases and reference lists for all original data on bilingualism and inhibitory control, with a cut-off date of April 30, 2020. Following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) protocols, 21 original studies were eligible to be included in this review. Results: The review yielded little evidence of bilingual inhibitory control advantage with different patterns of results for response inhibition and interference suppression. The heterogeneous outcomes might be related to individual differences, such as age and methodological issues, such as the use of different tasks. Conclusion: This literature review found heterogeneous results regarding the bilingual advantage in response inhibition and interference suppression. It stresses the importance of accounting for possible modulating factors when investigating the relationship between bilingualism and inhibition. If significant progress is to be made, accounting for confounding factors and reevaluating the inhibitory control measurement is required. Keywords: bilingual advantage, inhibitory control, interference suppression, response inhibition
... Bialystok et al. (2008) used a spatial Stroop task to compare the performance of bilinguals and monolinguals, and found that bilinguals had significantly better performance in the interference effect of inhibition. Recent studies also found that high-proficient bilinguals tend to have higher cognitive inhibition than low-proficient bilinguals (Tran et al., 2019;Xie and Zhou, 2020). ...
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Bilingualism has been shown to be associated with creativity, but the mechanisms of this association are not very well understood. One possibility is that the skills that bilinguals use in switching back and forth between languages also promote the cognitive processes associated with creativity. We hypothesized that high-proficient Chinese-English bilinguals would show higher convergent and divergent thinking than low-proficient bilinguals, with the differences being mediated by cognitive inhibition and cognitive flexibility, respectively. Chinese university students ( N = 54) were classified as high-proficient ( n = 27) and low-proficient ( n = 27) bilinguals based on their performance on the National English Test for College Students. As expected, group comparisons showed that the high-proficient group had higher scores on the Remote Associates Test (RAT, convergent thinking) and the Torrance Test of Creative Thinking (TTCT, divergent thinking). Also as expected, the association between bilingualism and convergent thinking was mediated by scores on a Stroop task (cognitive inhibition), and the association between bilingualism and divergent thinking was mediated by scores on a More-odd shifting task (cognitive flexibility). These findings suggest that bilingual learning can promote the development of different components of creativity through stronger cognitive inhibition and cognitive flexibility. The results provide empirical evidence for the relationship and mechanism between bilingual learning and creativity.
... 1.42 When we zoom in on some aspect of the growth spiral moving right down toward the microscopic level and beyond, we can follow some aspects of the amazing journey of normally developing children as they discover, decipher, and eventually deploy and use the grammar of their own native language(s). If any human babies happen to have access to more than one language before and after their birth, the research shows that they can acquire two or more native languages simultaneously (Swain, 1972;van den Noort et al., 2019;Xie & Zhou, 2020). Also, the research makes clear that our language capacity equips us equally well to acquire any language to which we may gain sufficient access through a community of speakers of that language. ...
Book
Full-text available
The human language capacity stands at the very top of the intellectual abilities of us human beings, and it ranks incommensurably higher than the intellectual powers of any other organism or any robot. It vastly exceeds the touted capacities of "artificial intelligence" with respect to creativity, freedom of will (control of thoughts and words), and moral responsibility. These are traits that robots cannot possess and that can only be understood by human beings. They are no part of the worlds of robots and artificial intelligences, but those entities, and all imaginable fictions, etc., are part of our real world... True narrative representations (TNRs) can express and can faithfully interpret every kind of meaning or form in fictions, errors, lies, or nonsensical strings seeming in any way to be representations. None of the latter, however, can represent even the simplest TNR ever created by an intelligent person. It has been proved logically, in the strictest forms of mathematical logic, that all TNRs that seem to have been produced by mechanisms, robots, or artificial intelligence, must be contained within a larger and much more far-reaching TNR that cannot be explained mechanistically by any stretch of imagination. These unique constructions of real intelligence, that is, genuine TNRs, (1) have the power to determine actual facts; (2) are connected to each other in non-contradictory ways, and (3) are generalizable to all contexts of experience to the extent of the similarities of those contexts up to a limit of complete identity. What the logicomathematical theory of TNRs has proved to a fare-thee-well is that only TNRs have the three logical properties just iterated. No fictions, errors, lies, or any string of nonsense has any of those unique formal perfections. The book is about how the human language capacity is developed over time by human beings beginning with TNRs known to us implicitly and actually even before we are born. All scientific endeavors, all the creations of the sciences, arts, and humanities, all the religions of the world, and all the discoveries of experience utterly depend on the prior existence of the human language capacity and our power to comprehend and produce TNRs. Without it we could not enjoy any of the fruits of human experience. Nor could we appreciate how things go wrong when less perfect representations are mistaken, whether accidentally or on purpose, for TNRs. In biology, when DNA, RNA, and protein languages are corrupted, the proximate outcome is disorder, followed by disease if not corrected, and, in the catastrophic systems failures known as death in the long run. The book is about life and death. Both are dependent on TNRs in what comes out to be an absolute dependency from the logicomathematical perspective. Corrupt the TNRs on which life depends, and death will follow. Retain and respect TNRs and life can be preserved. However, ultimate truth does not reside in material entities or the facts represented by TNRs. It resides exclusively in the TNRs themselves and they do not originate from material entities. They are from God Almighty and do not depend at all on any material thing or body. TNRs outrank the material facts they incorporate and represent. It may seem strange, but the result is more certain, I believe, than the most recent findings of quantum physics. Representations are connected instantaneously. Symbol speed is infinitely faster than the speed of light. In the larger perspective of history, when TNRs are deliberately corrupted, the chaos of wars, pestilence, and destruction follows as surely as night follows day. The human language capacity makes us responsible in a unique manner for our thoughts, words, and actions. While it is true that no one ever asked us if we wanted to have free will or not, the fact that we have it can be disputed only by individuals who engage in a form of self-deception that borders on pathological lying, the kind that results when the deceiver can no longer distinguish between the actions he or she actually performed in his or her past experience and the sequences of events that he or she invented to avoid taking responsibility for those events, or to take credit for actions he or she never performed. On the global scale such misrepresentations lead to the sort of destruction witnessed at Sodom in the day of Abraham. That historical destruction has recently been scientifically revealed at the site of Tall el-Hammam in Jordan. More about that and all of the foregoing in the book. If you encounter errors, please point them out to the author at joller@bellsouth.net. Thank you.
... Evidence has shown that cognitive control is modulated by demographic factors like age, socio-economic status (SES), etc. (Xie and Zhou, 2020). Therefore, those demographic features of our participants were also collected. ...
Article
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Few studies have examined the role of cognitive control in processing ambiguity, let alone the roles of different components of cognitive control. In the current study, the English (L2) Sentence Processing Task and a series of cognitive control tasks were administered among 111 young adult Chinese–English bilinguals to investigate the influence of different components of cognitive control on garden path sentence comprehension, with other factors such as age, socio-economic status, and language proficiency strictly matched. Data analysis results showed a significant garden path effect on response times (RTs) and accuracy among all the participants. The results of independent t-test analyses revealed that the high working memory (WM) group was faster in ambiguity resolution, and so was the high monitoring group. However, there were no differences between the high and low inhibition and shifting groups in ambiguity resolution. These findings reveal that only certain aspects of cognitive control influence garden path sentence comprehension.
... A different approach is to abandon bilingual versus monolingual classification in favor of withingroup analyses of individual differences. Although rare, this approach is becoming more common (e.g., Soveri et al., 2011 ;Xie, 2018 ;Xie and Zhou, 2020 ). We contend, however, that those studies are relatively weak tests of the bilingual advantage hypothesis because they assume a parametric distribution of individual differences. ...
Article
Full-text available
The question of whether bilingual language experience confers a cognitive advantage is still open. Studies report that putative bilingual advantages can be accounted for by individual differences in socioeconomic class, immigration status, or culture. Such studies typically consider bilingual experience to be a categorical variable using parametric statistical analyses. However, bilingual experience is itself highly variable across individual participants in most studies reported to date. Here we test the hypothesis that bilingual experience has a direct effect on executive function by estimating the effect of L2 (English) experience on performance in the Simon and flanker tasks. Linear mixed-effects models were used to assess effects of bilingual experience on performance. Self-reported L2 proficiency was associated with reduced interference on the Simon task as well as faster global response times on the flanker task, suggesting some cognitive advantages during inhibitory control. We conclude that individual differences in bilingual language experience may explain the many contradictory findings in studies testing the veracity of the bilingual advantage.
... Moreover, we adopted the Chinese version of Ravens Matrices (Raven et al., 1977;Li, 1989) for the measurement of IQ, which is a widely recognized non-verbal test used to measure reasoning and fluid intelligence and is applicable to participants from all cultures, with the Cronbach's Alpha of reliability analysis = 0. 949. For participants' SES, we followed previous literature (Wermelinger et al., 2017;Xie and Zhou, 2020) by adopting their parental education (1-7) as an approximate indicator. Finally, we used the reading comprehension section from HSK -Hanyu Shuiping Kaoshi level 4 sample tests (we used level 4 because our participants reported to have approximately intermediate level prior to the test) as the Chinese Reading Comprehension Test. 1 HSK is China's national standardized test designed to assess the Chinese language proficiency of non-native speakers such as foreign students and overseas Chinese (Teng, 2017;Peng et al., 2021). ...
Article
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The study investigates whether learners’ demographics (e.g., age, education, and intelligence-IQ), language learning experience, and cognitive control predict Chinese (L2) reading comprehension in young adults. Thirty-four international students who studied mandarin Chinese in mainland China (10 females, 24 males) from Bangladesh, Burundi, Congo, Madagascar, Nigeria, Rwanda, South Africa, and Zimbabwe were tested on a series of measures including demographic questionnaires, IQ test, two cognitive control tasks [Flanker Task measuring inhibition and Wisconsin Card Sorting Test (WCST) measuring mental set shifting], and a Chinese reading comprehension test (HSK level 4). The results of correlation analyses showed that education, L2 learning history, L2 proficiency, and previous category errors of the WCST were significantly correlated with Chinese reading comprehension. Further multiple regression analyses indicated that Chinese learning history, IQ, and previous category errors of the WCST significantly predicted Chinese reading comprehension. These findings reveal that aside from IQ and the time spent on L2 learning, the component mental set shifting of cognitive control also predicts reading outcomes, which suggests that cognitive control has a place in reading comprehension models over and above traditional predictors of language learning experience.
... Indeed, these statistical techniques required more attention (cf. Bak et al., 2014;Xie and Zhou, 2020). ...
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Inhibition and shifting are two key components of domain‐general cognitive control. Numerous studies have investigated the neural substrates of both components, but it is still unclear whether the relevant brain regions are specifically involved in one specific component or commonly engaged in both components. Here, we addressed this question by using functional magnetic resonance imaging and a modified saccade paradigm that was effective to disentangle inhibition and shifting in one experiment. The results showed that both the middle frontal gyrus and left parietal lobe were involved in both components but the middle frontal gyrus was more active for the inhibition while the inferior parietal lobe was more active for the shifting processing. The outcome suggests that, although both regions are engaged in inhibition and shifting, each plays a dominant role in one component. These findings provide a further insight into the neural dissociation in inhibition and shifting, as well as a better explanation on the framework of unity and diversity from a neuropsychological viewpoint. This article is protected by copyright. All rights reserved.