Cross-linguistic Influence in Third Language Acquisition Acquisition of an artificial language by Arabic-English bilinguals

Abstract

Aims and Objectives: This thesis investigates how previously acquired languages, Arabic and English, play a role in acquiring morphosyntax in an artificial language (AL) at the early stages of third language acquisition (L3A). Examining how lexical and syntactic similarities between L3 and previously learned languages affect cross-linguistic influence (CLI) during L3 acquisition is the main aim of this research. Methodology: In this study, Arabic-English bilingual L3 learners were exposed to an artificial language with varying syntactic resemblance to their L1 and L2. Participants were evaluated using Subject-Verb-Object (SVO) and Verb-Subject-Object (VSO) sentence structures. The study also assessed them on the word order of Adjective-Noun (Adj-N) versus Noun-Adjective (N-Adj) to highlight differences between the two languages. Data and analysis: Data were analyzed using RStudio with a mixed-effects binomial logistic regression model. The chosen word orders (N-Adj / Adj-N) served as response variables. Predictors included group assignment (Group A with syntax congruent to both English and Arabic, and Group B primarily aligned with Arabic), English Proficiency Test scores, and age of onset of English acquisition (AoO). Items and participant IDs were included as random intercepts. Findings and conclusion: The findings supported the theoretical assumptions of the Linguistic Proximity Model (LPM). This model posits that both lexical and syntactic similarities significantly influence cross-linguistic influence (CLI). These results challenge theories that prioritize only lexical factors. Findings also reveal that participants who started learning English later were more likely to favor the Arabic word order (N-Adj). This highlights the influence of age of onset (AoO) on activating native language syntax and underscores the role of syntactic exposure in L3 acquisition. Significance: This study's results enhance our understanding of artificial language acquisition and provide valuable insights into the complexities of multilingualism, particularly in terms of cross-linguistic influences.