Is there a bilingual advantage in the ANT task? Evidence from children

Antón, Eneko; Duñabeitia, Jon Andoni; Estévez, Adelina; Hernández, Juan; Bastida-Castillo, Alejandro; Fuentes, Luis J.; Davidson, Douglas; Carreiras, Manuel

doi:10.3389/fpsyg.2014.00398

Cited by 186 publications

(236 citation statements)

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“…Hence, BFs allow for evaluating the strength of evidence not only for the presence of an association, but explicitly also for the absence of a proposed association. Accordingly, using BFs has become increasingly popular in the area of cognitive enhancement (e.g., Antón et al 2014;Clark et al 2017;De Simoni and von Bastian 2017;Guye and von Bastian 2017;Kirk et al 2014;Paap et al 2014;Sprenger et al 2013;von Bastian et al 2017;von Bastian and Oberauer 2013).Based on previous findings, we expected positive associations of motivation (Brose et al 2012), a growth mindset (Jaeggi et al 2014), and conscientiousness (Studer-Luethi et al 2012) with change in training performance. Regarding neuroticism, our expectations were less specific, given that previous literature reported evidence for a negative association of neuroticism with mean training performance and transfer effects, but not with training gains (e.g., Studer-Luethi et al 2012, 2016.…”

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confidence: 76%

Section: The Present Studymentioning

confidence: 99%

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Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

2017

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Cognitive training interventions have become increasingly popular as a potential means to cost-efficiently stabilize or enhance cognitive functioning across the lifespan. Large training improvements have been consistently reported on the group level, with, however, large differences on the individual level. Identifying the factors contributing to these individual differences could allow for developing individually tailored interventions to boost training gains. In this study, we therefore examined a range of individual differences variables that had been discussed in the literature to potentially predict training performance. To estimate and predict individual differences in the training trajectories, we applied Latent Growth Curve models to existing data from three working memory training interventions with younger and older adults. However, we found that individual differences in demographic variables, real-world cognition, motivation, cognitionrelated beliefs, personality, leisure activities, and computer literacy and training experience were largely unrelated to change in training performance. Solely baseline cognitive performance was substantially related to change in training performance and particularly so in young adults, with individuals with higher baseline performance showing the largest gains. Thus, our results conform to magnification accounts of cognitive change.Keywords Working memory training . Individual differences . Latent growth curve modeling Over the past decade, there has been an exploding interest in computer-based commercial Bbrain training^programs and in scientific evidence relating to the effectiveness of such interventions, triggered by promising results of working memory (WM) training gains generalizing to previously untrained cognitive abilities such as intelligence in both younger (e.g., Jaeggi et al. 2008) and older adults (e.g., Borella et al. 2010). Although the idea of improving general cognitive functioning within a few weeks is enticing, there is also accumulating evidence against a generalized effect of WM training (e.g., Clark et al. 2017;De Simoni and von Bastian 2017;Guye and von Bastian 2017;Sprenger et al. 2013). Even on the meta-analytic level, evidence is mixed regarding the effectiveness of cognitive training in both younger and older adults (e.g., Au et al. 2015;Dougherty et al. 2016;Karbach and Verhaeghen 2014;Kelly et al. 2014;Lampit et al. 2014;Melby-Lervåg and Hulme 2013;Melby-Lervåg et al. 2016;Schwaighofer et al. 2015;Soveri et al. 2017). Aside from design and methodological choices potentially explaining the diverging findings (e.g., Noack et al. 2009;Shipstead et al. 2012), many authors increasingly articulated the potentially important influence of individual differences on cognitive training trajectories and outcomes (e.g., Buitenweg et al. 2012;Guye et al. 2016;Könen and Karbach 2015;Shah et al. 2012;von Bastian and Oberauer 2014 Individual differences in cognitive functioning (e.g., Ackerman and Lohman 2006) and learning potential (e.g., Stern ...

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confidence: 76%

Section: The Present Studymentioning

confidence: 99%

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

2017

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“…This advantage, which is supported by many studies (Bialystok, 1999;Costa et al, 2008), has been communicated to the general public through significant media coverage (Bhattacharjee, 2012;Reville, 2014). Yet, several recent studies have failed to replicate this finding (Morton and Harper, 2007;Paap and Greenberg, 2013;Antón et al, 2014), leading many researchers to doubt its validity (de Bruin et al, 2015;Paap et al, 2016), and creating a division in the bilingualism research community between believers and skeptics (Bak, 2016;Bialystok, 2016;Titone et al, 2017). This ambiguous state of the literature is not limited to executive functioning.…”

Section: Introductionmentioning

confidence: 91%

Do Bilinguals Have an Advantage in Theory of Mind? A Meta-Analysis

Schroeder

2018

Front. Commun.

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Bilingualism might help children develop Theory of Mind, but the evidence is mixed. To address the disagreement in the literature, a meta-analysis was conducted on studies that compared bilingual and monolingual children on false belief and other Theory of Mind tests. The meta-analysis of 16 studies and 1,283 children revealed a small bilingual advantage (Cohen's d = 0.22, p = 0.050). A secondary analysis was conducted on studies (k = 8) that statistically adjusted the Theory of Mind scores to correct for a bilingual disadvantage in language proficiency. This secondary analysis indicated a medium-size bilingual advantage (Cohen's d = 0.58, p < 0.001). There was no evidence for publication bias in either analysis. Taken together, the results provide support for a beneficial effect of acquiring two languages on mental state reasoning. Explanations for this bilingual advantage, which include bilingual-monolingual differences in executive functioning, metalinguistic awareness, and socio-pragmatic abilities, are discussed.

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“…Departing from previous studies that have utilised a single task to assess executive processes (c.f., Antón, et al, 2014;Bialystok, Craik, Grady, Chau, Ishii, Gunji, & Pantev, 2005;Bialystok & Viswanathan, 2009;Duñabeitia et al, 2014;Kirk, Fiala, Scott-Brown, & Kempe, 2014;Prior & Gollan, 2011) we were keen to employ multiple tasks measuring various aspects of attention and working memory to help identify more precisely which aspects of cognition are privileged in bilingualism. Previous studies have differentiated two processes related to attentionone that facilitates suppression of irrelevant information and the other that aids inhibiting prepotent response tendencies (e.g., Bunge, Dudukovic, Thomason, Vaidya & Gabrieli, 2002).…”

Section: Overview Of Present Studymentioning

confidence: 99%