JOURNAL ARTICLE

Using Interdisciplinary Approach in Business English Courses for China's English Majors.

  • Published In: European Journal of Education, 2024, v. 59, n. 4. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Xie, Qing 3 of 3

Abstract

This study reports an empirical case study about using interdisciplinary approach in business English courses with 41 English majors in the Chinese university context. The methodologies are two‐stage surveys, teacher reflection and participant observation. The results show that participants most preferred using specialist vocabulary and cross‐cultural business communication as learning activities in using interdisciplinary approach. The challenges and difficulties in interdisciplinary learning included lack of professional vocabulary, business or interdisciplinary knowledge, business thinking skills and inadequate language skills. A majority of the participants perceived the interdisciplinary approach as effective, as they had improvements in business language, knowledge, communication and English ability. For improving and refining the interdisciplinary approach, participants suggested more practical and detailed business knowledge, practice‐based activities, oral simulation and role‐play activities, more detailed guidance and feedback in the writing tasks, more business cases with interesting videos, increasing Chinese native language explanation and producing a business English language corpus. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:European Journal of Education. 2024/12, Vol. 59, Issue 4, p1
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:0141-8211
  • DOI:10.1111/ejed.12782
  • Accession Number:181057382
  • Copyright Statement:Copyright of European Journal of Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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