Abstract and Figures

This study further explores the theme of bilingual creativity with the present focus on code-switching. Specifically, it investigates whether code-switching practice has an impact on creativity. In line with the previous research, selective attention was proposed as a potential cognitive mechanism, which on the one hand would benefit from extensive code-switching, and on the other, facilitate creative performance. One hundred and fifty-seven multilingual college students completed a code-switching attitudes and behaviors questionnaire, which served to select habitual and non-habitual code-switchers. These respective groups were compared on creativity and selective attention tests. Habitual code-switchers demonstrated greater innovative capacity than their non-habitual counterparts. However, these groups revealed no difference in selective attention. Moreover, the relationship between selective attention and innovative capacity was found only among non-habitual code-switchers. Further, code-switching induced by a particular emotional state and by a lack of specific vocabulary in a target language appeared to relate to increase in innovative capacity. The discussion of these results lays foundation for further empirical research investigating the role of bilinguals' code-switching in their creative capacity.
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The role of code-switching in bilingual creativity
Anatoliy V. Kharkhurin
a
*and Li Wei
b
a
Department of International Studies, American University of Sharjah, Sharjah, UAE;
b
Department
of Applied Linguistics and Communication, Birkbeck College, University of London, London, UK
(Received 2 September 2013; accepted 8 January 2014)
This study further explores the theme of bilingual creativity with the present focus on
code-switching. Specifically, it investigates whether code-switching practice has an
impact on creativity. In line with the previous research, selective attention was
proposed as a potential cognitive mechanism, which on the one hand would benefit
from extensive code-switching, and on the other, facilitate creative performance. One
hundred and fifty-seven multilingual college students completed a code-switching
attitudes and behaviors questionnaire, which served to select habitual and non-habitual
code-switchers. These respective groups were compared on creativity and selective
attention tests. Habitual code-switchers demonstrated greater innovative capacity than
their non-habitual counterparts. However, these groups revealed no difference in
selective attention. Moreover, the relationship between selective attention and
innovative capacity was found only among non-habitual code-switchers. Further,
code-switching induced by a particular emotional state and by a lack of specific
vocabulary in a target language appeared to relate to increase in innovative capacity.
The discussion of these results lays foundation for further empirical research
investigating the role of bilingualscode-switching in their creative capacity.
Keywords: creativity; bilingualism; code-switching
Introduction
The relationship between bilingualism and creativity has generated a substantial amount
of research over the last four decades (see overviews in Kharkhurin 2012; Ricciardelli
1992; Simonton 2008). This research, however, seldom addresses the defining feature of
bilingualism, namely, code-switching (CS) the alternation and mixing of different
languages in the same episode of speech production. Yet, CS has been argued to be a
creative act (Li 2011a,2011b,2013; Wei and Wu 2009). For example, linguists working
in the linguistic ethnography tradition replaced CS with other terms such as translangua-
ging to capture its creative and dynamic nature (see a review in Garcia and Wei 2014).
They investigated the use of translanguaging in diverse contexts, from literature and
drama, to pop songs, the new media, and public signs (Androutsopoulos, 2013a,2013b;
Chik 2010; Jonsson 2005; Sebba, Jonsson, and Mahootian 2012; Shohamy and Gorter
2008). These studies take CS not simply as a juxtaposition of different grammatical
structural elements, but as an expressive, creative, and often multimodal performance.
Yet, not all bilinguals code-switch, and not all code-switchers switch between
languages in the same way. Sociolinguists have long argued that CS is a context-sensitive
*Corresponding author. Email: akharkhurin@aus.edu
International Journal of Bilingual Education and Bilingualism, 2014
http://dx.doi.org/10.1080/13670050.2014.884211
© 2014 Taylor & Francis
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discourse strategy (Auer 1998; Gumperz 1982), and bilinguals acquire their languages in
different contexts, different manners and for different purposes; they have different
language combinations, proficiency levels, and attitudes toward CS. There are bilinguals
who were born into bilingual families and communities where CS is the norm. They have
never had a monolingual experience. Instead, CS is their habitual discourse mode, and
they would find it difficult if not entirely impossible to speak one language only. For
others, CS is a learned skill; they only do so in specific contexts, for specific reasons, and
with specific interlocutors. There are still others who move between bilingual and
monolingual modes as part of their everyday social experience (Grosjean 2001). They
code-switch in specific emotional states or for special effects (e.g. Dewaele and Wei
2014). Therefore, one might expect intergroup variations in the relationship between
CS and creativity. In particular, bilinguals who code-switch frequently and regularly, i.e.
habitual code-switchers (HCS), often produce highly innovative forms that incorporate
elements from different languages; moreover, they do so seemingly effortlessly. They can
therefore be expected to show greater creative performance than those who do not use CS
in their everyday practice, i.e. non-habitual code-switchers (NHCS). The present study
begins with such a hypothesis and looks at creative performance differences between
HCS and NHCS.
Sociolinguists have long been interested in what they call bilingual creativity those
creative linguistic processes, which are the result of competence in two or more
languages. For example, the designing of a text that uses linguistic resources from two or
more related or unrelated languages; and the use of verbal strategies including CS in
which subtle linguistic adjustments are made for psychological, sociological, and
attitudinal reasons (see Kachru 1985, for a review of early studies). These processes
are usually interpreted with reference to identity representation, or the so-called optimal
grammarof bilingual use (Bhatt 2008; Bhatt and Bolonyai 2011). Bhatia and Ritchie
(2008) reveal various facets of bilingual creativity through CS as it manifests itself in the
day-to-day verbal behaviour of a bilingual. They argue that CS is essentially an
optimizingstrategy rendering a wide variety of new meanings which the separate
linguistic systems are incapable of rendering by themselves. The creative capacity of the
bilingual mind/brain depends on the bilinguals ability to maintain both language
separation and language integration simultaneously.
What cognitive mechanisms may underlie the relationship between CS and creativity?
In psychometric tradition, creative thinking is perceived as an ability to initiate multiple
cycles of convergent and divergent thinking (Guilford 1967), which create an active,
attention-demanding process that allows generation of new, alternative solutions
(Mumford et al. 1991). The fundamental difference between convergent and divergent
thinking is that the former is a conscious, attention-demanding process, while the latter
occurs in the unconscious mind, where attention is defocused (e.g. Kasof 1997;
Mendelsohn 1976) and thought is associative (e.g. Koestler 1964; Mednick and Mednick
1967; Ward, Smith, and Vaid 1997). Divergent thinking involves a broad search for
information and the generation of numerous novel alternative answers or solutions to a
problem (Guilford 1967). Guilford associated the properties of divergent thinking with
four main characteristics: fluency (the ability to rapidly produce a large number of ideas
or solutions to a problem); flexibility (the capacity to consider a variety of approaches to
a problem simultaneously); elaboration (the ability to think through the details of an idea
and carry it out); and originality (the tendency to produce ideas different from those of
most other people). Factor analysis of these characteristics performed with several distinct
sociocultural samples (Kharkhurin 2008,2009,2011) revealed that they can be grouped
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together as two types of creative capacities: fluency, flexibility, and elaboration traits
seem to represent the ability to generate and to elaborate on various, often unrelated,
ideas, while the originality trait is likely to represent the ability to extract novel and
unique ideas. The first type is referred to as generative capacity; it addresses the ability to
activate a multitude of unrelated concepts and work through the concepts already
activated. The second type is referred to as innovative capacity; it accounts for the ability
to produce original and useful ideas. Recent studies demonstrated that bilinguals
developed these capacities to a greater extent than their monolingual counterparts.
Russian-English bilingual college students demonstrated greater generative capacity by
scoring higher than their English monolingual counterparts on the Abbreviated Torrance
Test for Adults (ATTA) measures of fluency, flexibility, and elaboration (Kharkhurin
2008). Farsi-English bilingual college students revealed greater innovative capacity than
their Farsi monolingual counterparts (Kharkhurin 2009). Among multilingual college
students, those with high proficiency in English revealed greater innovative capacity than
those with moderate proficiency in this language (Kharkhurin 2011). We will use this
classification in the present study and assess creativity in terms of generative and
innovative capacities.
Psychometric research provides evidence favoring bilingualscreative abilities (see an
overview in Kharkhurin 2012). A series of studies conducted in different geographic,
linguistic, and cultural locations identified several cognitive mechanisms potentially
underlying creative thinking (Kharkhurin 2011). Of particular interest to the present study
is the finding that a routine cognitive mechanism of selective attention on the one hand
seems to benefit from individualsuse of several languages, and on the other plays an
important role in their creative performance. Specifically, the inhibition of irrelevant
information seemed to enhance the innovative capacity. Is there a relationship between
selective attention and CS, which may modulate the impact of the latter on creative
performance?
Empirical findings report bilingualsadvantages on the nonverbal tasks requiring
control processes such as selective attention to relevant aspects of a problem, inhibition of
attention to misleading information, and switching between competing alternatives (see
Bialystok 2005,2009, for an overview). Enhanced selective attention seemed to have
benefited from bilingualsextensive practice with two active language systems. In
bilingual language processing, both languages become activated (e.g. Costa 2005;de
Groot, Delmaar, and Lupker 2000; Jared and Kroll 2001).
1
When bilinguals use a target
language, the linguistic representation of the other language is still active and may
interfere with the target ones. Simultaneous activation of both languages makes bilinguals
constantly focus on one language, inhibit another language or switch between languages
(Bialystok et al. 2005). Selective attention ensures noninterruptive processing in the target
language by attending to the representational system corresponding to this language and
disregarding the system associated with a non-target language. Thus, an extensive
practice with at least two active language systems may facilitate selective attention
engaged in solving the conflicts in lexical retrieval as was demonstrated by empirical
research (reviewed in Bialystok 2005,2009). These findings were supported by the
results of brain imaging studies revealing that experience with two languages leads to
systematic changes in frontal executive functions (e.g. Bialystok et al. 2005). Due to
cross-linguistic practice, bilinguals exercise crucial cognitive skills that enhance the
problem-solving abilities requiring attentional control to focus on relevant and to ignore
misleading cues. In a similar fashion, although unrelated to bilingualism per se, Kiesel
and her colleagues (2010) presented an overview of research utilizing task-switching
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paradigm to study cognitive control and task interference. These studies also converge on
the notion that the ability to control the switch encouraged by well-developed selective
attention seems to facilitate an individuals cognitive performance. Thus, these findings
suggest that active CS may provide extensive opportunities for selective attention.
Brain imaging studies also hinted at the potential relation between CS and selective
attention. Jackson et al. (2001) used event-related dense-sensor electroencephalography
recording techniques to examine the time course of language switching during a visually
cued naming task in which bilingual participants named digits in either their first or
second language. They found modulation of event-related electrical potential components
in frontal cortex, when engaged in language switching and in suppressing manual
response in a Go/No-Go reaction time task. These findings suggest that similar inhibitory
mechanisms are involved in both response suppression and language switching. A more
recent study (Abutalebi et al. 2007) used event-related functional magnetic resonance
imaging on highly proficient bilinguals while they listened to narratives containing
switched passagesthat could either respect or violate the constituents of sentence
structure. One of the findings demonstrated that a switch into a less-exposed language
triggered activity in subcortical structures and the anterior cingulate cortex, which are
presumably involved in selective attention.
Thus, if there is a relationship between CS and selective attention, it is prudent to
suppose that extensive CS practice may result in enhanced selective attention capacity,
which may potentially entail increase in creative performance. This consideration entails
two hypotheses: (1) extensive CS practice enhances creative performance; and (2)
extensive CS practice strengthens selective attention. To test these hypotheses, a group of
HCS was compared to a group of NHCS on a creativity test and a test of selective
attention. We expected to find CS group performance differences on both tests. In
addition, considering the exploratory nature of the present study, which represents the
first attempt at investigating the relationship between CS and creativity in bilinguals, we
tried to identify possible CS factors enhancing creativity.
Method
Participants
The participants were 157 American University of Sharjah (United Arab Emirates)
multilingual students (56 male and 101 female) aged between 16 and 24 (M= 20.07,
SD = 1.55) who were recruited from the General Psychology subject pool. The major
languages both first (L1) and second (L2) were English, Arabic, and Urdu: 93
participants were Arabic-English; 19 participants were English-Arabic; 14 participants
were Urdu-English; and five participants were English-Urdu; 26 others reported a
different language combination. Forty-two participants indicated that they speak three
languages and eight of them revealed knowledge of a fourth language, French being the
most common third and fourth languages.
Procedure
Participants had to complete two online questionnaires prior to the offline testing in the
laboratory setting: biographical questionnaire and the one reporting their CS behavior and
attitudes. In the laboratory, participants received a creativity test and a test of selective
attention presented in counter-balanced order. All assessments were presented in English.
Using English as language of testing was justified by the fact that participants were
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fluent in English as shown by their high self-assessment of linguistic abilities (M= 24.27,
SD = 3.66, out of 28.00, see below). The self-assessment seemed to provide a reliable
measure given that English is the language of instruction at this university and a language
of communication in this country. That is, although United Arab Emirates is located on
the Arabian Peninsula, the primary language of official as well as informal everyday
communication is English. The majority of the population are expatriates from different
countries whose primary language of communication is English.
Instruments
Biographical questionnaire
An Internet-based multilingual and multicultural experience questionnaire (http://surveys.
aus.edu/index.php?sid = 87644) was administered to determine participantslinguistic and
cultural backgrounds. They received a questionnaire that, among other issues, obtained
data on participantsplace of origin, languages they speak, their assessment of linguistic
skills in each of these languages, and age of acquisition of these languages. The
questionnaire also included Likert-type 7-point scales on which participants rated their
abilities in reading, writing, speaking, and listening in their respective languages. The
total self-rating score ranged from 0 to 28 for each language.
Self-report of code-switching attitudes and behaviors
An Internet-based Code-Switching Attitudes and Behaviors questionnaire (http://surveys.
aus.edu/index.php?sid = 39486) was administered to determine participantsCS attitudes
and behaviors (see paper version in Appendix 1). The questionnaire enabled us to obtain
data on, among other issues, the participantsrate of CS, possible reasons why they code-
switch, and the emotional states and various circumstances in which they are likely to
code-switch. The first question asked the participants to select one out of five answers
concerning whether they code-switch when speaking with other bilinguals; the answers
were presented in the order of descending frequency of CS. Participantsanswers to this
question were used to assign them to HCS and NHCS. Four Likert-type 7-point scales
(see Appendix 1, items 47) assessed their CS frequency in a sentence, in a conversation,
unintentional, and intentional, respectively. Participants also had to indicate on eight
Likert-type 7-point scales (see Appendix 1, item 10) the likelihood of CS in various
circumstances. Participantsanswers to these questions were used to confirm the group
assignment. Additionally, participants were asked to select up to four reasons why they
switch languages (item 8: in a particular emotional state, to better convey a message, to
achieve special communicative effects, due to lack of a word in target language). They
also had to indicate on eight Likert-type 7-point scales (see Appendix 1, item 9) which
emotional states influence their likelihood to switch languages. The Likert-type scales
ranged from 3 to 3 for 7-point, and from 2 to 2 for 5-point, respectively. Other
questions addressed participantsCS attitude and were not used in the present analysis.
Assessment of creativity
Participantscreative abilities were assessed using the ATTA (Goff and Torrance 2002).
The ATTA was developed on the basis of the Torrance Tests of Creative Thinking
(Torrance 1966). It consists of activities utilizing the same rationale as activities in the
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original test, but in abbreviated form and requires considerably less testing time, which is
particularly beneficial when administering it to adults.
The standard ATTA has three paper-and-pencil activities preceded by written
instruction that explains general guidelines and encourages participants to use their
imagination and thinking abilities. In Activity 1, participants were asked to suppose that
they could walk on air or fly, and then to identify the troubles that they might encounter.
This activity provided verbal fluency and originality scores. In Activity 2, participants
were presented with two incomplete figures (see Appendix 2.1) and were asked to draw
pictures with these figures and to attempt to make these pictures as unusual as possible.
This activity provided figural fluency, originality, and elaboration scores. In Activity 3,
the participants were presented with a group of nine triangles arranged in a 3 × 3 matrix
(see Appendix 2.2) and were asked to draw as many pictures or objects as they could
using those triangles. This activity provided figural fluency, originality, elaboration, and
flexibility scores.
The standard ATTA assessment consists of four divergent thinking traits: fluency,
originality, elaboration, and flexibility. Fluency measures the ability to produce quantities
of ideas, which are relevant to the task instructions. The sum of fluency scores in all three
activities provided a fluency raw score. Originality measures the ability to produce
uncommon ideas, or ideas that are totally new or unique. The sum of originality scores in
all three activities provided an originality raw score. Elaboration measures the ability to
embellish ideas with details. The sum of elaboration scores in Activities 2 and 3 provided
an elaboration raw score. Finally, flexibility measures the ability to process information or
objects in different ways, given the same stimulus. A flexibility raw score was obtained
from Activity 3. The raw scores for fluency, originality, elaboration, and flexibility
obtained in the test were subsequently transformed into scaled norm-referenced scores by
the recommended procedure (Goff and Torrance 2002), which took age-related norms
into account. The ATTA manual reports the Kuder-Richardson (KR21) reliability
coefficient for the total raw score for the four traits measured by the ATTA as .84.
Two independent raters assessed participantscreative thinking abilities using the
standard ATTA assessment procedure (Goff and Torrance 2002). The significantly high
inter-rater correlation between the four norm-referenced scores produced by both raters
(r= .93 for fluency; r= .99 for originality; r= .97 for elaboration; and r= .93 for
flexibility, all ps < .001) indicated that the raters used the same rationale, and their ratings
were comparable. Subsequently, the respective scores produced by both raters were
averaged.
Table 1. Pearson correlations and factor loadings for the norm-referenced ATTA scores (N= 157).
Divergent thinking measures Factor loadings
23 4 III
1. Fluency .60*.42*.05 .85 .17
2. Flexibility .51*.09 .87 .06
3. Elaboration .22** .73 .36
4. Originality .02 .96
Note: The highest loadings of the measures are italicized. *p< .001; **p< .01.
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Generative and innovative capacities. Similar to the previous studies (e.g. Kharkhurin
2008,2009,2011), four ATTA norm-referenced scores were entered into a principle
component factor analysis with varimax rotation. The first three columns of Table 1
present the inter-correlations among the norm-referenced ATTA scores. The analysis
extracted two factors (whose eigenvalues exceeded 1), which accounted for 77.54% of the
variance. Loadings of the measures on these factors appear in the last two columns of
Table 1. The first factor was determined by the ATTA measures of fluency, flexibility, and
elaboration and represented the generative capacity. The second factor represented the
innovative capacity with the highest loading on originality. Subsequently, each factor
score was transformed into a new variable, thereby creating generative capacity and
innovative capacity scores, respectively. The Anderson and Rubins(1949) method of
estimating factor score coefficients was used to ensure orthogonality of the estimated
factors. The scores ranged from 1.46 to 2.76 for generative capacity and 1.65 to 1.85
for innovative capacity (both Ms = 0.00, SDs = 1.00), with higher scores representing
greater creative capacities. These scores were used in further analyses.
Assessment of selective attention
Selective attention was assessed by a version of the standard Eriksen flanker task (Eriksen
and Eriksen 1974). In this test, participants were first presented with a fixation cross for
500 ms, which was immediately followed by a horizontal array of five equally sized and
spaced arrows for 1700 ms. The array was 14.87 cm wide and 1.16 cm high. The stimuli
were presented in black-on-white background using 19? flat monitor. Participants were
instructed to attend to the central arrow and ignore the four flankers. They were to press
the left key for a left-facing central arrow and the right key for a right-facing central
arrow. The flanking arrows either all pointed in the same direction as the target arrow, or
they all pointed in the opposite direction. The trials on which the flanking arrows pointed
in the same direction as the target arrow were the congruent trials; the trials in which they
pointed in the opposite direction were the incongruent trials. Subjects received a total of
80 trials (40 congruent and 40 incongruent ones) in a random order, requiring an equal
number of left or right responses. The experiment was preceded by 12 practice trials;
participants had to obtain 85% of correct responses before continuing with the
experiment. The Eriksen flanker task lasted approximately 10 min. The Flanker score
reflected a proportional reaction time increase in the condition that required suppression
of the irrelevant information. That is, it was calculated as a reaction time difference
between incongruent and congruent conditions divided by their sum. The greater Flanker
score value indicates lower suppression capacity and therefore weaker selective attention.
Results
Habitual vs. non-habitual code-switchers
As explained above, to test our hypotheses we identified two CS groups: HCS and
NHCS. Participants who responded with option 1 or 2 to the question on CS frequency
(see Appendix 1, item 1) were assigned as the HCS. Participants who responded with
options 4 or 5 to this question were considered as not CS and were grouped as the NHCS.
Participants who selected option 3 were considered as infrequently CS and were excluded
from the analysis. Table 2 presents mean responses of participants in each group to the
questions assessing their CS behaviour. All three groups showed highly significantly
different results on all questions (all ps < .001) with the HCS obtaining the highest, the
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NHCS the lowest, and excluded group the middle scores. These results confirmed the
propriety of our group selection, and these groups were used in further analysis.
Selective attention and creativity in CS groups
To test our hypotheses, we looked at selective attention and creative performance
differences between two selected CS groups. Table 3 presents mean Flanker, generative,
and innovative capacity scores of the HCS and NHCS groups. The HCS significantly
outperformed the NHCS on the measure of innovative capacity (F(1, 109) = 6.14, p<
.05, η
2
= .05). No group differences were observed either for generative capacity or for
selective attention. In addition, as Table 3 demonstrates, there were no differences
between L1 and L2 groupsself-ratings as well as their age of acquisition of both
languages, which eliminated a potential effect of covariance.
Although the first hypothesis was confirmed, we did not find support for the second
one. The HCS group demonstrated no differences in selective attention with the NHCS
group. In an attempt to find an explanation for this finding, we performed some additional
testing. A repeated-measure analysis of variance (ANOVA) revealed an interaction effect
of CS group and the frequency with which participants switch between languages
(intentionally, unintentionally). The NHCS indicated a higher intentional CS rate than
unintentional one, whereas the HCS indicated a reverse tendency (F(1, 109) = 4.95, p<
Table 2. Group size, mean age (with standard deviations), and mean scores (with standard
deviations) on selected Code-Switching Attitudes and Behaviors questionnaire items assessing CS
behavior of HCS, NHCS, and those excluded from the analysis.
HCS NHCS Excluded F(2, 154)
N89 22 46
Age 20.17 (1.49) 19.91 (1.74) 19.96 (1.61) 0.42
CS within sentence (item 4) 0.55 (1.42) 2.05 (1.05) 0.80 (1.05) 43.65*
CS within conversation (item 5) 1.06 (1.33) 1.68 (0.72) 0.24 (1.10) 52.77*
CS unintentionally (item 6) 0.98 (1.47) 1.73 (1.32) 0.46 (1.33) 39.11*
CS intentionally (item 7) 0.65 (1.35) 1.18 (1.30) 0.54 (1.36) 22.59*
CS in various circumstances (averaged
over eight questions of item 10)
0.66 (0.64) 0.00 (0.89) 0.48 (0.58) 8.76*
Note: The last column presents ANOVAsF-values. *p< .001.
Table 3. HCS and NHCS code-switchersmean scores (with standard deviations) on Flanker,
generative, and innovative capacities (transformed scores), L1 and L2 self-ratings, and age of L1 and
L2 acquisition.
HCS NHCS
Flanker 0.06 (0.04) 0.06 (0.03)
Generative capacity 0.10 (0.90) 0.17 (1.09)
Innovative capacity 0.10 (1.04)*0.51 (0.93)
L1 self-rating 24.60 (4.35) 24.32 (5.40)
L2 self-rating 23.94 (3.89) 22.32 (5.77)
Age of L1 acquisition 4.44 (2.76) 4.44 (2.58)
Age of L2 acquisition 5.55 (2.94) 5.11 (3.05)
Note: *p< .05.
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.05, η
2
= .04). This finding suggests that the NHCS group is more prone to controlled CS
and therefore may reveal a more pronounced language switch costs effect than the HCS
group.
Therefore, we analyzed the relationship between selective attention and creativity in
each group separately. The NHCS revealed a highly significant correlation between the
Flanker score and the innovative capacity (r=.47, p< .05), whereas the HCS showed
no significant correlation between these measures. The negative correlation suggests that
the enhanced innovative capacity in the NHCS is related to greater suppression capacity.
CS factors enhancing creativity
Further, we explored what factors in CS behavior may facilitate innovative capacity of
the HCS. With this group, we performed an ANOVA with four reasons for CS (see
Appendix 1, item 8) as independent factors and innovative capacity as the dependent
variable. We found a significant interaction between CS due to lack of a word in target
language and CS in a particular emotional state (F(1, 88) = 4.61, p< .05, η
2
= .06). As
Figure 1 demonstrates, only HCS participants who indicated that they code-switch when
in a particular emotional state and when lacking a word in the target language obtained
greater innovative capacity compared to others, although the effect did not reach
significance (ps ranging from .11 to .38). Unfortunately, this analysis cannot be
performed on the NHCS due to its small size (e.g. there was only one participant who
reported CS in a particular emotional state and when lacking a word in the target
language).
Figure 1. The effect of interaction between the CS in particular emotional state and the CS due to
lack of a word in target language on the innovative capacity of the HCS, N= 89.
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Finally, a logistic regression analysis was conducted with the HCS group to predict
CS in a particular emotional state using the frequency with which various emotional
states influence likelihood to switch languages (see Appendix 1, item 9) as predictors.
A test of the full model against a constant-only model was statistically significant,
indicating that the predictors as a set reliably distinguished between participants who
switch in particular emotional state and those who do not (χ
2
= 17.33, p< .05 with
df = 8). The Wald criterion demonstrated that only alertness made a significant
contribution to prediction (p= .04). This finding indicates that participants are likely to
switch languages in the state of alertness.
Discussion
This study continues a line of research investigating various aspects of bilingual creativity
(Kharkhurin 2012). The present article focuses on the role of bilingualsCS in their
creative performance. The results confirmed the major hypothesis of the study by
showing greater innovative capacity in bilinguals who code-switch frequently and
regularly as compared to their counterparts who do not code-switch in their everyday
practice. This finding can be explained by a two-fold argument. First, the studies
reviewed in the introduction demonstrate a relationship between CS and selective
attention. Second, Kharkhurin (2011) found that the inhibition of irrelevant information,
which appears to be an important selective attention mechanism, was related to
enhancement in bilingualsinnovative capacity. Therefore, extensively CS bilinguals
should outperform their counterparts who do not code-switch on the measure of
innovative capacity; this is what the results of the present study show. However, if this
line of reasoning holds, we would expect greater selective attention in the HCS group.
Our findings though revealed this not to be the case; rather, we found no difference in
selective attention between HCS and NHCS. Moreover, the relationship between selective
attention and innovative capacity found in the previous study appeared only among
NHCS. One possible explanation is that HCS and NHCS differ in their language switch
cost. Behavioral studies of language switching in bilinguals provided evidence that there
is a significant and measurable response time cost associated with switching from one
language to another, and that this cost is observed even when switching is entirely
predictable (Meuter and Allport 1999). Research also shows that language switch cost is
observed with controlled, involuntary switching (e.g. Costa and Santesteban 2004; Gollan
and Ferreira 2009; Macizo, Bajo, and Paolieri 2012). It then follows that the NHCS is
more likely to reveal the language switch cost effect. This means that participants in this
group need to make an additional use of selective attention to compensate for language
switch cost. Those with relatively more elaborate selective attention capacity demon-
strated greater innovative capacity. These findings, therefore, can contribute to the
development of a more general model of cognitive control of CS (e.g. Green and
Wei, 2014).
Note that the present study presents an attempt to initiate a line of research
investigating the relationship between CS and creativity. Considering the exploratory
nature of the study, we looked at potential CS factors, which may contribute to
enhancement in bilingualscreativity. Two CS conditions were found to be facilitatory for
creative functioning. Specifically, CS induced by a particular emotional state and by
insufficient vocabulary in the target language appeared to relate to increase in innovative
capacity. The relatedness of these two CS conditions can be speculatively addressed by
our finding that alertness was the only significant predictor for emotion-triggered CS.
10 A.V. Kharkhurin and L. Wei
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Alertness, for example, may be heightened during temporary loss for words in a particular
language, which in turn triggers CS. Alertness may also require more selective attention,
which is connected to innovative capacity. This finding provides an interesting account,
in which emotion-triggered CS results in activation of creative capacities. Recent research
on the relationship between bilingualism and emotions provided evidence that CS is often
triggered by the speakers emotions and other affective factors (e.g. Dewaele 2010b;
Pavlenko 2005). Dewaele (2008,2010a), in particular, showed that bilinguals code-
switch to specific language to express love, anger, and frustration. Our finding suggests
that this kind of emotion-triggered CS could be connected to creativity. This may be
because CS breaks the conventional conversational routine by introducing different,
emotionally laden elements of language. Needless to say though that these conclusions
are far too preliminary and any account of these findings should be considered as highly
speculative.
Conclusion
As stated in the Introduction, a major objective of the present study is to introduce a new
theme to the scientific investigation of bilingual creativity. We have fulfilled this purpose
as our findings provide the empirical basis for further research on the relationship
between CS, the defining characteristic behavior of bilingual speakers, and their creative
capacities.
As an exploratory study, this one has some limitations. It is evident that assessment of
language-related practices using self-report questionnaires may mask certain effects. This
method can be safely utilized in assessment of linguistic aptitude due to the fact that self-
reports have been demonstrated to adequately reflect language abilities (e.g. Albert and
Obler 1978; Macnamara 1967,1969). Unfortunately, this may not be true for CS. This
practice involves both conscious and unconscious processes, which participants may not
be aware of. We recognize that the information we use to assign the participants into the
two groups is self-report rather than actual behaviour. Sociolinguists who have studied
bilingualsattitudes toward CS have revealed certain level of under-reporting by those
who view CS as a sign of linguistic deficiency. But over-reporting of CS has not been
reported by any researcher. While there may be participants in our NHCS group who
code-switch more often than they self-reported, there is no reason for us to believe that
the HCS group with its substantial size is not reliable. Nevertheless, introducing more
objective measures of CS seems to be prudent in future research, especially when it
comes to differentiation of HCS and NHCS. For example, participants can be engaged in
a specifically constructed dialog, which prompts CS in different conversational contexts
(e.g. to express emotions, to achieve special communicative effects, when lacking a word
in the target language).
Further, some people may see the size of the NHCS group not large enough to draw
reliable conclusions. Although N= 22 is not a large number indeed, it appears to provide
sufficient statistical power. A comparison between HCS and NHCS gained significant
results, and the correlational analysis of the NHCS group produced such a high rthat
even with a relatively small number, it obtained significance.
Thus, once the empirical foundation for the relationship between CS and creativity is
established, further research is required to build an elaborate framework. What is the role
of CS in bilingual creativity? What cognitive mechanisms and psychological states may
have an impact on this relationship? These are just a few fundamental questions that
researchers will need to answer. Another question that needs to be further explored is
International Journal of Bilingual Education and Bilingualism 11
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pertinent to the relationship between CS and selective attention. Does CS require more or
less selective attention? Although the answer to this question seems to be straightforward,
it may present a key to any model building for bilingual cognition.
Further, one may be interested in looking at how various emotional states are related
to CS. Earlier we have speculated that the state of alertness may be triggered by
temporary loss for words in a particular language, which in turn facilitates CS. There is
emerging evidence to suggest that some multilinguals code-switch more frequently in
certain emotional states (Dewaele and Wei 2014). Research by Pavlenko (2005) and
Dewaele (2010b) indicates that the relationships between emotion and particular
languages in the multilinguals linguistic repertoire are complex and multidimensional.
Some emotions may trigger more CS in some multilinguals, while in others they may
trigger inhibition of particular languages. In other words, different emotional states may
facilitate or inhibit CS, which in turn may have ramifications for creative capacities. A
new line of research on the role of emotions in bilingual creativity (Kharkhurin and
Altarriba, 2011) provides evidence of the interactive effect of the mood (positive vs.
negative) and linguistic context (use of dominant vs. subordinate language) on an
individuals creative performance. Thus, future studies may explore potential effects of
emotions, specific languages, and CS on creativity.
Last but not least, the ideas presented in this study have important implications for
pedagogy. The role of CS in multilingual education has already received a substantial
consideration in linguistic ethnography tradition in the context of above-mentioned
translanguaging in teaching and learning (see Garcia and Wei 2014, for a detailed
discussion). Our results contribute with a cognitive perspective. Kharkhurin (2012)
argued that CS can be detrimental for interference suppression (a manifestation of
selective attention capacity), which in turn may harm creative thinking. A logical
conclusion from this argument called for discouraging students from CS. In fact, this
statement initiated a discussion between the authors of the present work, which gave rise
to this empirical study. The findings clearly demonstrate that CS has no impact on
selective attention; moreover, HCS revealed advantages in creative thinking compared to
NHCS. Thus, instead of discouraging CS in a multilingual classroom (or in a multilingual
household), researchers and educators should develop strategies encouraging this
practice. This initiative can be supported by a systematic study of cognitive mechanisms
underlying creative thinking, which could be strengthened by CS, and those conditions
that may facilitate it.
Acknowledgments
We are grateful to the participants of the study without whom this project could never have been
done. We are also grateful to the participants of the 9
th
International Symposium on Bilingualism in
Singapore in 2013 for their constructive feedback. The comments from three anonymous reviewers
for the journal have helped to improve the quality of the presentation of this article immensely. We
are especially grateful to Jean-Marc Dewaele, the editor of the journal, for his support,
understanding, and advice.
Note
1. This integrated lexicon approach to the bilingual memory is contrasted with an alternative view
that advocates a language-specific access system in which both languages are stored separately
and activation of one language does not entail the activation of the other (Gerard and
Scarborough 1989; Soares and Grosjean 1984).
12 A.V. Kharkhurin and L. Wei
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Appendix 1: Code-switching attitudes and behaviors
1. Do you switch between languages when speaking with other bilinguals (those who speak the same languages
as you)? Check one
(1) Every time I speak with another bilingual.
(2) Almost every time I speak with another bilingual.
(3) Occasionally when I speak with other bilinguals.
(4) I hardly do this when I speak with other bilinguals.
(5) I never code-switch. I always maintain ONE language consistently in my conversations
with other bilinguals.
2. How many languages do you speak?
3. Please indicate below each of your languages and rate from 1(lowest)to10 (highest) how well you can
maintain a conversation in this language without using your other languages.
4. How often do you switch between different languages within one sentence?
Never Rare Not often Sometimes Often Very often Always
5. How often do you switch between different languages within one conversation?
Never Rare Not often Sometimes Often Very often Always
6. How often do you switch between languages unintentionally?
Never Rare Not often Sometimes Often Very often Always
7. How often do you switch between languages intentionally?
Never Rare Not often Sometimes Often Very often Always
International Journal of Bilingual Education and Bilingualism 15
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8. If you do switch, why do you think you do this? Mark all that applies
(1) I switch to another language when I am in a particular emotional state.
(2) Although I know words in both languages, I still switch to another language to convey
my message better (with more precision).
(3) Although I know words in both languages, I still switch to another language to say something
unusual, to achieve special communicative effects.
(4) I switch to another language when I dont know a word in a language I currently speak.
9. How often do the following emotional states influence your likelihood to switch languages (i.e. do any of the
options make you more or less likely to switch)?
Never Rare Not often Sometimes Often Very often Always
(1) Happiness
(2) Excitement
(3) Affection
(4) Alertness
(5) Tiredness/
Fatigue
(6) Anger
(7) Anxiety
(8) Stress
10. How likely would you switch languages in various circumstances?
Very
unlikely
Quite
unlikely
Neutral Quite
likely
Very
likely
(1) When a monolingual (someone who does not speak
one of your languages) joins the conversation.
(2) When I am re-telling a story/joke that occurred in a
particular language.
(3) When the person with whom I am speaking,
switches between languages.
(4) When I do not have the vocabulary to express in a
particular language.
(5) When the concept I am discussing doesnt exist in a
particular language.
(6) If I do not want other people in the vicinity to
understand what I am saying.
(7) If I feel the person with whom I am speaking, will
have trouble understanding what I am saying.
(8) When I am trying to represent myself in a certain
way, as belonging to a certain group.
16 A.V. Kharkhurin and L. Wei
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Appendix 2: Abbreviated Torrance Test for Adults
(1) Stimuli for Activity 2
(2) Stimuli for Activity 3
International Journal of Bilingual Education and Bilingualism 17
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La creatividad es el santo grial de las ciencias cognitivas y tiene especial importancia para los investigadores de las ciencias de la computación y la inteligencia artificial. Es obvio que la creatividad forma parte esencial de la inteligencia, a pesar de que la mayoría de estudios que intentan explicarla o incluso replicarla han fallado. En el presente artículo proponemos dos aproximaciones innovadoras: por un lado, entender los procesos cognitivos como seguidores de reglas o heurísticas, a pesar de hacerlo de una manera flexible o incluso contradictoria o caótica, pero que nos dirige en cualquier caso a un contexto de uso desacomplejado de multiheurísticas, que es lo que hemos denominado la «cognición mixta»; por otro lado, proponemos un mecanismo poco explorado de forma general en la literatura académica cognitiva para servir de punto de apoyo entre los modelos antiguos y una visión alternativa: la abducción. Mediante estas dos estrategias, a la vez que analizando casos específicos relacionados con la capacidad creativa de los seres humanos, podemos vislumbrar un nuevo paradigma cognitivo más realista y sincero con las capacidades humanas, hecho que permitirá en un futuro no muy lejano el diseño de sistemas de razonamiento artificiales más potentes y complejos.
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