Integrating Digital Technologies for Vocabulary Error Identification and Correction among Business Chinese Majors at Thuongmai University

Abstract

In the context of digital transformation in higher education and the increasing demand for professionals proficient in Business Chinese, enhancing students’ Chinese vocabulary competence has become an essential objective in language education. This study investigates vocabulary errors produced by students majoring in Business Chinese at Thuongmai University in order to identify common types of errors and analyze their underlying causes. Based on these findings, the study proposes a model for integrating digital technologies into the process of lexical error identification and correction in order to improve the effectiveness of teaching and learning Chinese vocabulary. Employing a mixed-methods approach that combines both qualitative and quantitative analyses, the study demonstrates that the application of digital technologies—such as language corpora, artificial intelligence (AI), adaptive learning systems, and online learning platforms—can effectively support students in detecting and correcting vocabulary errors. The findings indicate that the systematic integration of digital technologies not only helps learners use vocabulary more accurately and appropriately in context, but also contributes to the innovation of Business Chinese teaching methodologies toward a more modern and personalized approach.