Abstract
We present an exact replication of Experiment 2 from Kovács and Mehler's 2009 study, which showed that 7-month-old infants who are raised bilingually exhibit a cognitive advantage. In the experiment, a sound cue, following an AAB or ABB pattern, predicted the appearance of a visual stimulus on the screen. The stimulus appeared on one side of the screen for nine trials and then switched to the other side. In the original experiment, both mono- and bilingual infants anticipated where the visual stimulus would appear during pre-switch trials. However, during post-switch trials, only bilingual children anticipated that the stimulus would appear on the other side of the screen. The authors took this as evidence of a cognitive advantage. Using the exact same materials in combination with novel analysis techniques (Bayesian analyses, mixed effects modeling and cluster based permutation analyses), we assessed the robustness of these findings in four babylabs (N=98). Our results did not replicate the original findings: although anticipatory looks increased slightly during post-switch trials for both groups, bilingual infants were not better switchers than monolingual infants. After the original experiment, we presented additional trials to examine whether infants associated sound patterns with cued locations, for which we did not find any evidence either. The results highlight the importance of multicenter replications and more fine-grained statistical analyses to better understand child development. HIGHLIGHTS: We carried out an exact replication across four baby labs of the high-impact study by Kovács and Mehler (2009). We did not replicate the findings of the original study, calling into question the robustness of the claim that bilingual infants have enhanced cognitive abilities. After the original experiment, we presented additional trials to examine whether infants correctly associated sound patterns with cued locations, for which we did not find any evidence. The use of novel analysis techniques (Bayesian analyses, mixed effects modeling and cluster based permutation analyses) allowed us to draw better-informed conclusions.
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