An Empirical Analysis of the Impact of Voice-driven Conversational AI Function on English Speaking Skills of Vocational College Students
Year: 2024
Type: article
Abstract: This study investigates the impact of real-time voice-driven conversational AI function on the English-speaking proficiency of vocational college students. The sample includes second-year E-commerce and Business English majors at a vocational college in Guangdong Province. Using pre- and post-tests and surveys, the study assesses the function’s effectiveness across six core dimensions: language proficiency, motivation, and interest, learning strategies and habits, technology acceptance and user experience, learning outcomes, and confidence and anxiety in English learning. The findings indicate that the function significantly enhances students’ English-speaking proficiency and fosters greater learning interest and confidence. Analysis shows that students from different academic backgrounds exhibit varied outcomes: Business English majors achieve greater improvements in fluency and confidence, while E-commerce majors show more notable gains in technology acceptance and learning motivation. Additionally, the AI tool effectively reduces anxiety during oral communication and boosts overall engagement in English learning. This study provides empirical support for integrating voice-driven conversational AI into English instruction in vocational colleges.
Author: Buyuan Ye
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4408511727