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Adaptive Control Hypothesis On Bilingual Advantage

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Table of contents

  1. Abstract
  2. Adaptive Control Hypothesis
  3. Materials and Measures
  4. Data Processing
  5. Results
  6. Discussion
  7. References

Abstract

This study investigates the presence, or lack thereof, of a bilingual advantage in inhibition control and executive processing while considering the different interactional contexts as per the adaptive control hypothesis posited by Green and Abutalebi (2013). 849 University of Melbourne students enrolled in an undergraduate psychology course participated in this study. The data was collected through a Flanker task and an online questionnaire that sorted participants into the appropriate interactional contexts of monolingual, single-language, and dual-language contexts. The Flanker effect was calculated and a one-way ANOVA test and post-hoc tests were used to examine any significant differences between the three groups. No significant differences were found between the baseline monolingual group or the bilingual groups of both interactional contexts, in contrast to previous literature that supports a domain-general bilingual advantage. It thus prompts further research into whether a non-behavioural difference between monolinguals and bilinguals of various interactional contexts may exist.

Adaptive Control Hypothesis

The field of research regarding the potential advantages of bilingualism on cognitive processing is wide and varied, investigating the age-old question as to whether learning additional languages holds any benefits. A wealth of literature supports the claim of a bilingual advantage, with bilinguals performing significantly better than monolinguals on tasks that measure inhibitory control, task-switching, or working memory (Bialystok, Craik, Green, & Gollan, 2009).

The reason behind this alleged bilingual advantage lies the innate tendency to process prompts even in the language not actively used, as demonstrated in a study by Guttentag, Haith, Goodman, & Hauch (1984). Bilinguals had a significant delay in response time when presented with peripheral information in their second language, indicating a simultaneous activation of both languages despite the given context. Building off this theory, Bialystok et al. (2009) posits that the joint activation of both languages forces bilinguals to constantly inhibit unnecessary information from the irrelevant language, consequently developing more refined domain-general inhibitory control processes than monolinguals.

From a non-behavioural perspective, a neuro-imaging study found that when compared to monolinguals, bilinguals were more efficient in utilising the anterior cingulate cortex, an area typically associated with domain-general executive function, thus supporting how inhibition of a non-relevant language is plausibly generalised (Abutelabi et al.,2012). Similarly, an examination of the effects of bilingualism on a task-switching exercise found that bilinguals were significantly faster than monolinguals when switching between tasks, suggesting a proficiency that indicates better developed cognitive control (Garbin et al., 2010).

Notably, most studies involve young adults, who typically perform better than children or older adults on tasks that test executive processing (Friedman, Nessler, Cycowicz, & Horton, 2009). An extension of investigation into older adults still found that older bilinguals consistently performed better on tasks that involved greater utilisation of working memory (Bialystok, Craik, Klein, & Viswanathan, 2004).

Other studies hold more critical views on the subject. Paap and Greenberg (2013) tested for the bilingual advantage through the Flanker and Simon tests, discovering not only a lack of significant differences in measurements of the bilingual advantage in their studies, but also a disadvantage in bilinguals’ executive processing. A meta-analysis of 152 consolidated studies bears similar inconclusive results (Lehtonen et al., 2018). Thus, the ambiguity of the topic prompts the consideration of alternative approaches.

Most studies consider bilingualism as a whole, with little differentiation within the group itself. Green and Abutalebi (2013), however, introduce the Adaptive Control Hypothesis (ACH) as a means of differentiating between the ways bilinguals interact with others under situational circumstances. They propose that the processes required to resolve joint activation problem differs per interactional context. Bilinguals whose language use differs per environment fall into the ‘single-language context’, while bilinguals whose language use differs per conversational partner within the same environment fall into the ‘dual-language context’. A third context was also proposed, called the ‘dense code-switching context’, wherein the speaker uses both languages within the same interaction. The different demands on language control processes contributes to a variation on the level of demand on the cognitive system, prompting further study with attention paid to a distinction between interactional contexts.

This study thus aims to investigate whether the consideration of the ACH aids in demonstrating a possible bilingual advantage. In the case of the present study, the term ‘bilinguals’ includes individuals who speak more than one language fluently. In testing via the Flanker effect, it is hypothesised that (a) bilinguals in the single-language context will demonstrate an advantage in inhibition control over monolinguals, and (b) bilinguals in the dual-language context will demonstrate an advantage in inhibition control over monolinguals and bilinguals in a single-language context.

Materials and Measures

Participants first completed a standard arrow Flanker task adapted from Fan, McCandliss, Sommer, Raz, and Posner (2002). On each trial, a fixation cross appeared for 500 ms, which was then replaced by a line of five arrows. Participants were instructed to make a left or right button-press response according to the direction in which the central arrow was pointing, and to ignore the arrows on both sides of the central arrow, which were pointing in either the same or the opposite direction to the target. The arrows remained on-screen until a response was made, and the time from stimulus presentation until response was recorded. In the event of an incorrect response, the word “WRONG” was presented for 800 ms before the next trial began; no feedback was given for correct responses. The intertrial interval was 1000 ms. There were 120 trials in total (60 congruent trials and 60 incongruent trials), divided across four blocks of 30 trials each, with accuracy displayed at the end of each block. The trial order was randomized for each participant.

Participants then completed a questionnaire about their language background and usage. They were asked to list the languages they spoke, and to rate their proficiency in and frequency of use of each language from one to ten. Then, they were given a list of seven common situations and were asked to rate their agreement from one to seven with three items for each situation: “I tend to speak to some people in one language, and other people in a different language”, “I tend to only speak in one language”, and “I tend to use more than one language within one sentence”. These items reflected the dual-language, single-language, and dense-code switching interactional context, respectively. The scores for each situation were weighted according to the percentage of time participants estimated themselves to spend in each situation in a given week, and then scores for each item were summed across all situations to produce a total score for each of the three items.

Data Processing

Participants who achieved below 80% accuracy on the Flanker task were excluded from analyses, resulting in the loss of 1 (0.12%) participant. Of those remaining, RTs faster than 200 ms or slower than 1000 ms were excluded from the analyses, which resulted in 0.58% of trials lost. A Flanker Effect (FE) was calculated for each participant by computing the average RT for correct trial responses in each of the congruent and incongruent conditions and then subtracting the average for the congruent condition from the average for the incongruent condition.

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For the language questionnaire, participants were classified as monolingual if they reported speaking only one language or if they reported speaking more than one language but rated their proficiency or frequency of use in their additional languages as two or less. The remaining participants were classified into the dual-language, single-language, or dense code-switching context based on the corresponding item on which they scored the highest. Participants who fell into the dense code-switching group were then excluded from the analyses. To ensure a balanced design, 182 participants were then randomly selected from the two largest groups in order to match the size of the smallest group, giving 182 participants in each group.

Results

The Flanker effect was calculated by finding the difference between the mean RT in congruent and incongruent trials. Monolinguals had the smallest FE of all three, while the dual-language had the largest FE.

A one-way ANOVA test was used to identify any significant differences in magnitude between any of the three trials. The analysis found no statistically significant differences between the means, as well as a small effect size as per Cohen’s (1988) rule of thumb, F(2, 543) = 2.96, p = 0.53, η2 = .01. However, considering the lack of specificity regarding differences between the groups in the ANOVA test, post-hoc tests with Bonferroni corrections were also conducted to examine the differences in greater detail.

Post-hoc tests revealed no significant differences between the monolingual and single-language contexts (MD = .07, p = 1.00). Furthermore, no significant differences were found between the monolingual and dual-language contexts (MD = 4.15, p = .102). No significant differences were also found between the single-language and dual-language contexts (MD = 4.08, p = .112).

Discussion

The results from the study revealed no significant differences between the monolingual and single-language contexts, the monolingual and dual-language contexts, nor the single-language and dual-language contexts. Thus, both hypotheses, that (a) the single-language context would demonstrate an advantage over monolinguals, and (b) bilinguals in the dual-language context would demonstrate an advantage over monolinguals and bilinguals in a single-language context, were not supported by the findings.

The lack of significant results are somewhat surprising, and seemingly at odds with the wealth of research that supports a bilingual advantage. If the arguments for a domain-general bilingual advantage are true, then it would be likely to identify significant behavioural differences in the monolingual and bilingual cases in both interactional contexts (Bialystok et al., 2009; Abutalebi et al., 2012). However, the non-significant results of the present study appear to suggest otherwise, prompting further investigation into the reasons that lie behind such.

In considering the ACH, the present study accounted for differences in interactional contexts. It may have left other factors unaccounted for, potentially either overlooked or unfeasible for the scope of this study.

The characteristics of the present participants may have played a role in influencing the results of the study. The participants for the study were students enrolled in a second-year psychology course at the University of Melbourne. Despite the cultural diversity of the cohort, a sample that draws from a university group could still run the risk of homogenization, for example in terms of cognitive ability or age range, further contributing to smaller and less significant differences between monolinguals and bilinguals. Furthermore, an average accuracy of 98.26% was observed in the Flanker task, which could indicate a potential ceiling effect that skews results.

Another methodological factor that may have influenced the results could have been the number of trials conducted. Granted the large number of both congruent and incongruent trials, participants may have become familiar enough with the task to the extent of rendering the bilingual advantage non-significant, as theorised by Hilchey and Klein (2011).

In terms of how the present study relates to prior studies, the findings appear to support that of Paap and Greenberg (2013), who were unable to replicate previous studies on the bilingual advantage. Measuring inhibitory control through the Flanker test, they were unable to find any trend significantly indicative of a bilingual advantage, with any differences being rather marginal. Instead, they found data that suggested a monolingual advantage instead, which, upon further examination, appears to be somewhat supported by the present study’s data as well -- despite bilinguals seeming to have an advantage in mean reaction times, they have a marginal global disadvantage in their FE scores. Though it falls beyond the scope of the current study, it is possible that an examination of other highly fluent bilinguals, such as the dense code-switching bilinguals, may offer additional insight.

Furthermore, the non-significant results thus seem to indicate the absence of observable behavioural differences in the bilingual advantage. Electrophysiological study, which was beyond the scope of the present study, was examined by Kousaie and Phillips (2012) to identify any potential non-behavioural differences. They found inconsistent variations in the electrophysiological data, and posited that processing differences varied across their usage of the Stroop, Simon, and Flanker tasks. With this in mind, it is possible that differences between monolinguals and the two bilingual interactional contexts may benefit from being examined not only through other tasks such as the Simon and Stroop tasks, but also in terms of electrophysiological or neuro-imaging data, which allows an investigation beyond behavioural measures.

The non-significance of the results collected in this study provide further insight into the controversial topic at hand, adding to the cases against a coherent bilingual advantage, and seemingly contributing to a balance between the two opposing sides. The present study seeks to bolster the current field of literature by building upon and testing Green and Abutalebi’s (2013) adaptive control hypothesis on a behavioural basis. In doing so, it opens up opportunities for further research into the conditions that draw out the bilingual advantage, if there is one at all, perhaps eventually leading to a more conclusive board of information to resolve the question of whether learning multiple languages is truly beneficial.

References

  1. Abutalebi, J., Della Rosa, P.A., Green, D.W., Hernandez, M., Scifo, P., Keim, R., Cappa, S.F., & Costa, A. (2012). Bilingualism Tunes the Anterior Cingulate Cortex for Conflict Monitoring. Cerebral Cortex, 22(9), 2076–2086.
  2. Bialystok, E., Craik, F., Green, D., & Gollan, T. (2009). Bilingual Minds. Psychological Science in the Public Interest, 10(3), 89-129.
  3. Bialystok, E., Craik, F. I. M., Klein, R., & Viswanathan, M. (2004). Bilingualism, Aging, and Cognitive Control: Evidence From the Simon Task. Psychology and Aging, 19(2), 290-303.
  4. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge.
  5. Friedman, D., Nessler, D., Cycowicz, Y.M., Horton, C. (2009). Development of and change in cognitive control: A comparison of children, young adults, and older adults. Cognitive, Affective, & Behavioral Neuroscience, 9(1), 91-102.
  6. Garbin, G., Sanjuan, A., Forn, C., Bustamante, J.C., Rodriguez-Pujadas, A., Belloch, V., Hernandez, M., Costa, A., & Avila, C. (2010). Bridging language and attention: Brain basis of the impact of bilingualism on cognitive control. NeuroImage, 53(4), 1272-1278.
  7. Green, D. W., & Abutalebi, J. (2013). Language control in bilinguals: The adaptive control hypothesis. Journal of Cognitive Psychology, 25(5), 515-530.
  8. Guttentag, R. E., Haith, M. M., Goodman, G. S., & Hauch, J. (1984). Semantic processing of unattended words by bilinguals: A test of the input switch mechanism. Journal of Verbal Learning & Verbal Behavior, 23(2), 178-188.
  9. Hilchey, M.D., & Klein, R.M. (2011). Are there bilingual advantages on nonlinguistic interference tasks? Implications for the plasticity of executive control processes. Psychonomic Bulletin & Review, 18(4), 625-658.
  10. Kousaie, S., & Phillips, N.A. (2012). Conflict monitoring and resolution: Are two languages better than one? Evidence from reaction time and event-related brain potentials. Brain Research, 1446, 71-90.
  11. Lehtonen, M., Soveri, A., Laine, A., Järvenpää, J., de Bruin, A., Antfolk, J. (2018). Is bilingualism associated with enhanced executive functioning in adults? A meta-analytic review. Psychological Bulletin, 144(4), 394-425.
  12. Paap, K.R., & Greenberg, Z.I., (2013). There is no coherent evidence for a bilingual advantage in executive processing. Cognitive Psychology, 66(2), 232-258.
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Adaptive Control Hypothesis On Bilingual Advantage. (2021, September 09). Edubirdie. Retrieved March 29, 2024, from https://edubirdie.com/examples/adaptive-control-hypothesis-on-bilingual-advantage/
“Adaptive Control Hypothesis On Bilingual Advantage.” Edubirdie, 09 Sept. 2021, edubirdie.com/examples/adaptive-control-hypothesis-on-bilingual-advantage/
Adaptive Control Hypothesis On Bilingual Advantage. [online]. Available at: <https://edubirdie.com/examples/adaptive-control-hypothesis-on-bilingual-advantage/> [Accessed 29 Mar. 2024].
Adaptive Control Hypothesis On Bilingual Advantage [Internet]. Edubirdie. 2021 Sept 09 [cited 2024 Mar 29]. Available from: https://edubirdie.com/examples/adaptive-control-hypothesis-on-bilingual-advantage/
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