AI Language Alchemists: Unleashing Task-Based Chatbots to Enhance Speaking Proficiency,Shape Attitudes,and Foster a Translanguaging Space

Abstract

This study investigates the efficacy of task-based chatbots in enhancing speaking skills and shaping the attitudes toward language learning of L2 learners while fostering a translanguaging space. The research employs a mixed-methods approach through quantitative and qualitative data collection methods. A sample of 80 L2 learners participated in the study. Quantitative data were collected through pre- and posttests to measure speaking proficiency and a translanguaging scale to gauge L2 learners’ ability to transition seamlessly between languages. Qualitative data were gathered through semistructured interviews with the participants. The findings reveal a significant improvement in speaking proficiency among the learners following the chatbot interventions. Moreover, there was a positive shift in the learners’ attitudes, from negative to positive, toward L2 speaking proficiency. The qualitative analysis highlights creating a translanguaging space wherein the learners effectively utilize their linguistic repertoire to facilitate communication. The results underscore the importance of integrating chatbot technologies into language instruction to enhance engagement and foster authentic communication.

Keywords

task-based chatbot translanguaging space speaking proficiency artificial intelligence (AI)language learners

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