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A path to the bilingual advantage: Pairwise matching of individuals

Published online by Cambridge University Press:  10 April 2019

Sophia Czapka
Affiliation:
University of Potsdam, Human Sciences Faculty, Research group: Diversity and Inclusion, Potsdam, Germany
Christiane Wotschack
Affiliation:
University of Potsdam, Human Sciences Faculty, Research group: Diversity and Inclusion, Potsdam, Germany
Annegret Klassert
Affiliation:
University of Potsdam, Human Sciences Faculty, Research group: Diversity and Inclusion, Potsdam, Germany
Julia Festman*
Affiliation:
University of Potsdam, Human Sciences Faculty, Research group: Diversity and Inclusion, Potsdam, Germany Pedagogical University Tyrol, Innsbruck, Austria
*
Address for correspondence: Julia Festman, E-mail: julia.festman@ph-tirol.ac.at
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Abstract

Matching participants (as suggested by Hope, 2015) may be one promising option for research on a potential bilingual advantage in executive functions (EF). In this study we first compared performances in three EF-tasks of a naturally heterogeneous sample of monolingual (n = 69, age = 9.0 y) and multilingual children (n = 57, age = 9.3 y). Secondly, we meticulously matched participants pairwise to obtain two highly homogeneous groups to rerun our analysis and investigate a potential bilingual advantage. The initally disadvantaged multilinguals (regarding socioeconomic status and German lexicon size) performed worse in updating and response inhibition, but similarly in interference inhibition. This indicates that superior EF compensate for the detrimental effects of the background variables. After matching children pairwise on age, gender, intelligence, socioeconomic status and German lexicon size, performances became similar except for interference inhibition. Here, an advantage for multilinguals in the form of globally reduced reaction times emerged, indicating a bilingual executive processing advantage.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s) 2019
Figure 0

Table 1. Descriptive statistics for heterogeneous groups

Figure 1

Table 2. Descriptive statistics for homogeneous groups

Figure 2

Table 3. Correlations between background variables

Figure 3

Fig. 1. Mean response latencies (with error bars indicating standard errors) of the A) go/nogo task, B) BST and C) N-back for the heterogeneous groups (monolinguals - dark bars and multilinguals - light bars).

Figure 4

Table 4. Regression models for the EF tasks

Figure 5

Fig. 2. Mean response latencies (with error bars indicating standard errors) of the A) go/nogo task, B) BST and C) N-back for the heterogeneous groups (monolinguals - dark bars and multilinguals - light bars).