**Proposal: Finally doing bilingual cognitive control research right! (An online replication and extension of Khodos and Moskovsky (2020))
Dr Polly Barr
School of Psychological Science
Bilingual cognitive control research is a mess! Researchers have been debating bilingual cognitive effects for the past 25 years with inconclusive results. Retrospectively it is likely these inconclusive results were constrained by traditional lab testing: small sample size, availability, and type of bilinguals (i.e., whatever foreign language students were around) and time constraints (however long a participant could sustain attention for in an experimental session ~1 hour). Now with modern research practices (i.e., Prolificand Gorilla) we can conduct this research with adequate sample sizes and ‘true’ or different types of bilinguals and multiple tasks across numerous sessions.
If we can determine if there is a cognitive advantage, we can help delay dementia (by up to 5 years resulting in priceless economic and wellbeing benefits) and promote learning and understanding of cultures and immigration (which is needed now more than ever).
Recently it has been suggested that engaging in different types of cognitive control (i.e., proactive and reactive) can depending on language background (Calabria et al., 2020; Cattaneo et al., 2015; Morales et al., 2013, 2015). Proactive and reactive control have been robustly measured via the task-switching (Braver et al., 2020; Gullifer & Titone, 2020; Khodos et al., 2021; Prior & Macwhinney, 2010)(ref) and AXCPT paradigms (Braver et al., 2009, 2020; Gonthier et al., 2016; Liu et al., 2020; Morales et al., 2013, 2015). Moving away from the outdated monolingual comparison Khodos and Moskovsky (2020) found earlier onset of active bilingualism and dual language use was associated with reduced mixing costs (i.e., proactive control). Switching costs (i.e., reactive control) were associated with dual language use only. This illustrates how the variation within a bilingual population (i.e., at what age they became bilingual and use of both languages) can result in difference in cognitive control.
Considering the replication crisis, and the vast amount of inconclusive evidence regarding bilingual cognitive control (potentially due the issues mentioned above) a replication and extension of Khodos and Moskovsky (2020) is vital to confirm that this finding is reproducible and valid.
We aim to replicate and extend Khodos and Moskovsky (2020) finding that age of onset of bilingualism and dual language predict cognitive control. Like Khodos and Moskovsky (2020) we will measure participants cognitive control through a key-press task switching paradigm, however we will also extend this to also measure participants cognitive control through a task-switching mousetracking paradigm (mousetracking has the unique ability to measure online decision making and therefore uniquely tap into the time course of cognitive control) and through AXCPT. By measuring cognitive control through numerous tasks will add construct validity which is essential in cognitive control research.
Like Khodos and Moskovsky (2020) we will use the Language and Social background questionnaire(Anderson et al., 2018) to measure a participants dual language use. However, unlike Khodos and Moskovsky (2020) this questionnaire will be used as an eligibility criterion to the study. Both single use and dual language use participants will be eligible to the study, but they will be invited on a 1:1 ratio to ensure we have matched groups on sample size. Participants will be invited to take part in two ~60 minute experimental tasks with a delay of at least 24 hours. This will ensure we are able to administer multiple cognitive tasks without participants concentration affecting the results. Using the smallest effect size from Khodos and Moskovsky (2020) (.254) but with a more conservative significance level (.001) and the calculation pwr.f2.test(u =5, f2 =.44/(1-.44), sig.level = 0.001 , power = 0.8 ) from the pwr package R results in a sample size of 76.2183. Therefore 77 participants will be used as a minimum sample size recruitment per experiment however Bayesian analysis (liner mixed effects) will be employed as a stopping rule (i.e. when BF01/10 >3). Given that most studies are deemed under powered post-data collection we will aim to collect double our minimum sample size or a BF01/10 >3 whichever is achieved first. Full methods and statistical analysis plan is available here osf.io/4puqj, however briefly we will mimic Khodos and Moskovsky (2020) by modelling participants cognitive control scores (proactive and reactive cognitive control scores) against various different bilingual (including age of bilingualism onset and dual language use) and sociodemographic predictors (e.g. SES, age etc) in a backward stepwise regression for each task (Task-switch key press, task-switch mousetracking, proactive AXCPT and Reactive AXCPT).
We predict that we will replicate Khodos and Moskovsky (2020) and find that reduced mixing costs (proactive control) are predicted by younger age of bilingualism onset and dual-language use, whereas reduced switching costs (reactive control) will only be predicted by dual-language use in the task-switch key press paradigm. We predict that the same findings will be replicated in the extension tasks.
Initially we will run a pilot study of 20 participants to ensure the paradigms work and assess the attrition rate between the three experimental sessions (pre-screener, session 1 and session 2). We will then run two studies. In the first study, like Khodos and Moskovsky (2020) we will restrict our sample to English L2 speakers residing in an English-speaking country (UK, America, Australia). The second study will run exactly the same but with a non-restricted bilingual population to see if the findings are generalisable to other bilingual populations.
This study is the ideal study to run on prolific as we can restrict our study to bilinguals from all around the world and pre-screened for dual language use, type of bilingualism and country of residence to collate large sample sizes, across multiple sessions. Previously online studies have been more applicable to social psychology studies, but given recent advancement in experimental platforms this an excellent time to utilise the benefits of online testing for experimental cognitive science. You can find the preregistration of this project here osf.io/4puqj and all the raw anonymised data and R analysis code will be freely available on Github.
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