Reform and Effectiveness Analysis of an Industry-Oriented Business Russian Curriculum System

Main Article Content

L. L. Ma

Abstract

This study examines the reform and effectiveness of an industry-oriented Business Russian curriculum designed to address the persistent disconnect between classroom instruction and authentic business contexts. A 16-week teaching experiment was conducted with 96 Business Russian majors divided equally into an experimental group and a traditional teaching group. The reformed curriculum reconstructed course objectives around business task completion, reorganized teaching content into industry-based modules, introduced authentic and adapted materials from cross-border e-commerce, international logistics, contract operations, financial settlement, and after-sales service, and integrated progressive classroom tasks, teacher feedback, peer review, revision, and comprehensive performance assessment. Course effectiveness was evaluated through terminology recognition, business writing, information extraction, translation revision, oral interaction, and overall achievement. The experimental group obtained an average comprehensive score of 83.9, compared with 74.2 in the traditional teaching group. It also achieved 84.6% in industry terminology recognition, 86.2 points in business writing, 87.4% in text information extraction, and a 79.8% success rate in oral interaction tasks. These findings indicate that an industry-oriented curriculum can strengthen students’ ability to process Business Russian texts, apply specialized terminology, revise written output, and complete communicative tasks in realistic business situations.

Downloads

Download data is not yet available.

Article Details

How to Cite
Ma, L. L. (2026). Reform and Effectiveness Analysis of an Industry-Oriented Business Russian Curriculum System. Advanced Electromagnetics, 15(3), 10949–10960. https://doi.org/10.7716/aem.v15i3.4305
Section
Research Articles

References

W. A. Farea and M. K. M. Singh, “A target English needs analysis on ESP course: Exploring medical students’ perceptions of necessities at a Yemeni university,” Training, Language and Culture, vol. 8, no. 1, pp. 20–37, 2024.

P. Sureeyatanapas, N. Srisawasdi, and P. Sureeyatanapas, “A need analysis of English proficiency in engineering graduates: perspectives of the world’s leading companies in Thailand,” European Journal of Engineering Education, vol. 49, no. 6, pp. 1179–1202, 2024.

M. M. Roshid and A. Kankaanranta, “English communication skills in international business: Industry expectations versus university preparation,” Business and Professional Communication Quarterly, vol. 88, no. 1, pp. 100–125, 2025.

P. V. Sysoyev, “Development of the Russian as a foreign language teachers’ methodological competence in the artificial intelligence era,” Russian Language Studies, vol. 24, no. 1, pp. 71–86, 2026.

Y. Liu and W. Ren, “Task-based language teaching in a local EFL context: Chinese university teachers’ beliefs and practices,” Language Teaching Research, vol. 28, no. 6, pp. 2234–2250, 2024.

I. L. Damayanti, P. Derinalp, F. Asyifa, et al., “Exploring English for Academic Purposes program: Needs analysis and impact evaluation,” Studies in English Language and Education, vol. 11, no. 3, pp. 1616–1635, 2024.

L. Shen, L. J. Zhang, and S. Carter, “Understanding doctoral students’ needs for thesis discussion writing and supervisory curriculum development: A sociocultural theory perspective,” Language, Culture and Curriculum, vol. 37, no. 4, pp. 456–471, 2024.

M. E. Poehner and X. Lu, “Sociocultural Theory and Corpus-Based English Language Teaching,” TESOL Quarterly, vol. 58, no. 3, pp. 1256– 1263, 2024.

L. Bryfonski, Y. Y. Ku, and A. Mackey, “Research methods for IDS and TBLT: A substantive and methodological review,” Studies in Second Language Acquisition, vol. 46, no. 3, pp. 617–643, 2024.

M. East and D. Wang, “Advancing the communicative language teaching agenda: what place for translanguaging in task-based language teaching?” The Language Learning Journal, vol. 53, no. 6, pp. 702–714, 2025.

S. Jia and M. Bava Harji, “Themes, knowledge evolution, and emerging trends in task-based teaching and learning: A scientometric analysis in CiteSpace,” Education and Information Technologies, vol. 28, no. 8, pp. 9783–9802, 2023.

T. Han and E. Sari, “An investigation on the use of automated feedback in Turkish EFL students’ writing classes,” Computer Assisted Language Learning, vol. 37, no. 4, pp. 961–985, 2024.

N. Loukachevitch, E. Artemova, T. Batura, et al., “NEREL: a Russian information extraction dataset with rich annotation for nested entities, relations, and wikidata entity links,” Language Resources and Evaluation, vol. 58, no. 2, pp. 547–583, 2024.

E. Sari and T. Han, “The impact of automated writing evaluation on English as a foreign language learners’ writing self-efficacy, self-regulation, anxiety, and performance,” Journal of Computer Assisted Learning, vol. 40, no. 5, pp. 2065–2080, 2024.

H. Shi and V. Aryadoust, “A systematic review of AI-based automated written feedback research,” ReCALL, vol. 36, no. 2, pp. 187–209, 2024.

T. Yamashita, “Exploring potential biases in GPT-4o’s ratings of English language learners’ essays,” Language Testing, vol. 42, no. 3, pp. 344–358, 2025.

I. A. Khabutdinov, A. V. Chashchin, A. V. Grabovoy, et al., “RuGECToR: Rule-based neural network model for Russian language grammatical error correction,” Programming and Computer Software, vol. 50, no. 4, pp. 315– 321, 2024.

B. Lyu, C. Lai, and J. Guo, “Effectiveness of chatbots in improving language learning: a meta-analysis of comparative studies,” International Journal of Applied Linguistics, vol. 35, no. 2, pp. 834–851, 2025.

S. Al-Farsi and Z. Slimi, “Impact of Teacher and Peer Feedback on University Students’ Spelling and Punctuation,” European Journal of English Language Studies, vol. 5, no. 2, pp. 113–128, 2025.

K. W. H. Tai and Y. V. Zhao, “Success factors for English as a second language university students’ attainment in academic English language proficiency: Exploring the roles of secondary school medium-of-instruction, motivation and language learning strategies,” Applied Linguistics Review, vol. 15, no. 2, pp. 611–641, 2024.

X. Huang, D. Zou, G. Cheng, et al., “Trends, research issues and applications of artificial intelligence in language education,” Educational Technology & Society, vol. 26, no. 1, pp. 112–131, 2023.

M. Bassett and L. Macnaught, “Embedded approaches to academic literacy development: A systematic review of empirical research about impact,” Teaching in Higher Education, vol. 30, no. 5, pp. 1065–1083, 2025.