Optimization Strategies for the Stereoscopic Intersection Teaching Mode of Language in the Context of Business Management
DOI: https://doi.org/10.62517/jnme.202410326
Author(s)
Angyou Jiang
Affiliation(s)
English Language Department, Faculty of Modern Languages and Communication, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Abstract
In the context of the era of globalization and digitalization, the demand for talent in the field of business management is no longer limited to single skills. In addition to mastering master solid business management knowledge, it is also necessary to possess excellent cross-cultural communication skills to integrate into the international market environment. This paper elaborately analyzes how to apply the optimized stereoscopic intersection teaching mode of language in the context of business management education to improve students’ language application skills more efficiently and enable students to cope with ease in the complex and changeable environment of international business.
Keywords
Business Management, Language, Stereoscopic Intersection, Teaching Mode, Optimization
References
[1] Wang Yuya, Bai Xinfang. Research on the Teaching Practice of Higher Vocational Business English Courses Integrated with Ideological and Political Elements - Taking the Foreign Trade English Correspondence Course as an Example [J]. Modern Vocational Education, 2024, (17): 85-88.
[2] Liu Xiao. Business English: Achieving Effective Communication in the Transnational Business Environment [J]. Kaoshi Yu Zhaosheng, 2024, (Z1): 108-109.
[3] Zhou Jinhua, Zhang Hengmao. Research on Business English Translation of Foreign Trade-oriented Papermaking Enterprises Based on the Functional Equivalence Theory [J]. Paper Science and Technology, 2024, 43(03): 153-156. DOI: 10.19696/j.issn1671-4571.2024.3.036.
[4] Zhong K, Wang Y, Pei J, et al. Super efficiency SBM-DEA and neural network for performance evaluation[J]. Information Processing & Management, 2021, 58(6): 102728.
[5] Jan N, Gwak J, Pei J, et al. Analysis of networks and digital systems by using the novel technique based on complex fuzzy soft information[J]. IEEE Transactions on Consumer Electronics, 2022, 69(2): 183-193.
[6] Yu Z, Pei J, Zhu M, et al. Multi-attribute adaptive aggregation transformer for vehicle re-identification[J]. Information Processing & Management, 2022, 59(2): 102868.
[7] Li J, Li S, Cheng L, et al. BSAS: A Blockchain-Based Trustworthy and Privacy-Preserving Speed Advisory System[J]. IEEE Transactions on Vehicular Technology, 2022, 71(11): 11421-11430.