Code-Mixing and Second Language Acquisition on Social Media by Digital Native Indonesian Children.

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Bibliographic Details
Title: Code-Mixing and Second Language Acquisition on Social Media by Digital Native Indonesian Children.
Authors: Rustan, Edhy1, Ajiegoena, Andi Muhammad1
Source: Theory & Practice in Language Studies (TPLS). Jan2023, Vol. 13 Issue 1, p217-226. 10p.
Subject Terms: *Digital media, *Second language acquisition, *Social media, Indonesians, Digital natives, Speech
Abstract: The aims of this study are to (1) explain the forms of mixed-use of L1 to L2 codes in social media posts, (2) explain the factors that cause the use of L1 to L2 mixed codes and (3) describe language mastery. This study uses a qualitative descriptive analysis method. Data in code-mixing was obtained from secondary data, namely written posts with COVID-19 content on social media, Facebook and Twitter. A mixture of L1 and L2 codes in postings on social media includes words and phrases manifested in congruent insertion, change, and lexicalisation forms. The influencing factors are divided into (1) speaker factors, such as showing off, prestige, and language skills, and (2) linguistic factors, such as popular terms, topics, modes, speech partners, time and place/location. With the emergence of various terms related to COVID-19, the mastery of a second language for digital natives, in this case, English, is increasing. Although the use of code-mixing, there are some errors in writing, sentence structure, and cohesion, digital natives can master L2 through codemixing, including accuracy of word writing, word selection, syntactic structure, cohesion, and coherence in the sentence. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
Description
Abstract:The aims of this study are to (1) explain the forms of mixed-use of L1 to L2 codes in social media posts, (2) explain the factors that cause the use of L1 to L2 mixed codes and (3) describe language mastery. This study uses a qualitative descriptive analysis method. Data in code-mixing was obtained from secondary data, namely written posts with COVID-19 content on social media, Facebook and Twitter. A mixture of L1 and L2 codes in postings on social media includes words and phrases manifested in congruent insertion, change, and lexicalisation forms. The influencing factors are divided into (1) speaker factors, such as showing off, prestige, and language skills, and (2) linguistic factors, such as popular terms, topics, modes, speech partners, time and place/location. With the emergence of various terms related to COVID-19, the mastery of a second language for digital natives, in this case, English, is increasing. Although the use of code-mixing, there are some errors in writing, sentence structure, and cohesion, digital natives can master L2 through codemixing, including accuracy of word writing, word selection, syntactic structure, cohesion, and coherence in the sentence. [ABSTRACT FROM AUTHOR]
ISSN:17992591
DOI:10.17507/tpls.1301.25