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The effects of script variation, literacy skills, and immersion experience on executive attention: A comparison of matched monoscriptal and biscriptal bilinguals

Published online by Cambridge University Press:  22 December 2017

SUJIN YANG*
Affiliation:
Ewha Womans University
HWAJIN YANG
Affiliation:
Singapore Management University
ANDREE HARTANTO
Affiliation:
Singapore Management University
*
Address for correspondence: Sujin Yang, Ph.D., Department of Psychology, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul, South Korea, Postal Code: 03760sy98@cornell.edu
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Abstract

To examine script effects, monoscriptal Spanish–English (SE) bilinguals, who use two similar Roman alphabetic systems, were compared to biscriptal Chinese–English (CE) bilinguals, who use logographs and Roman alphabets. On the Attention Network Test, script effects were most evident in global processing efficiency (i.e., inverse efficiency and reaction time) and in the local network of executive control in favor of biscriptal CE bilinguals over matched monoscriptal SE counterparts. Literacy effects were found on the executive control network among Chinese–English bilinguals of high L1-literacy skills over their script- and immersion-matched counterparts, who varied only in low L1 literacy. In a similar vein, results of the multiple regression analysis demonstrated that script and literacy are significant predictors of executive control capacities. Our results suggest that script variation in a bilingual's language pair is an important modulating factor that enhances overall attention efficiency.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 
Figure 0

Table 1. Main mechanisms for script and literacy effects.

Figure 1

Table 2. Participant descriptions, bilingual language profiles, and levels of language proficiency (SDs).

Figure 2

Figure 1. Schematic representation of the Attention Network Test (ANT).

Figure 3

Figure 2. The effects of script variation on the IES, RT, and executive control measures.

Figure 4

Table 3. Global Measures of ANT Performance (SDs) and Network Efficiency.

Figure 5

Table 4. Summary of Multiple Regression Analyses to Predict Global Attention Measures and Local Attention Network Measures of ANT.