Role of AI-Driven Personalization in Enhancing English Language Achievement among Vocational College Students in China
List of Authors
  • Mohamad Jafre Zainol Abidin, Niu Yanyan

Keyword
  • AI Personalization, English Language Achievement, Vocational Education, AI-Assisted Activities, Frequency of Interaction

Abstract
  • This research examines the impact of AI-driven personalisation on improving English language proficiency among vocational college students in China. This research examines the impact of three independent variables—degree of AI personalisation, frequency of AI engagement, and nature of AI-assisted activities—on the dependent variable: English language achievement. A mixed-methods approach was utilised, integrating quantitative analysis of student performance data with qualitative insights derived from participant interviews. The results indicate that increased AI personalisation and regular engagement with customised activities markedly enhance language competency, especially in vocabulary development and listening comprehension. The nature of AI-assisted activities, including interactive exercises and feedback-driven assessments, is essential for motivating students and enhancing skill development. These findings highlight the capability of AI-driven educational technologies to meet individual learning requirements and enhance English language proficiency in vocational education settings

Reference
  • No Data Recorded