当代外语研究

当代外语研究 ›› 2025, Vol. 25 ›› Issue (3): 129-139.doi: 10.3969/j.issn.1674-8921.2025.03.012

• 人工智能与外语教育 • 上一篇    下一篇

基于大语言模型的高校俄语教材数智化教学探索——以《走遍俄罗斯1》为例

杨明明(), 王溪淙()   

  1. 上海交通大学,上海, 200240
  • 出版日期:2025-06-28 发布日期:2025-05-16
  • 作者简介:杨明明,上海交通大学外国语学院研究员、博士生导师。主要研究方向为俄苏文学与俄语教学。电子邮箱:yangmm@sjtu.edu.cn;
    王溪淙,上海交通大学外国语学院博士研究生。电子邮箱:wangxicong@sjtu.edu.cn
  • 基金资助:
    *2024年度上海交通大学AI+课程建设项目阶段性成果

Research on Digital-Intelligent Teaching of College Russian Textbooks Based on Large Language Models: A Case Study of The Way to Russia 1

YANG Mingming(), WANG Xicong()   

  • Online:2025-06-28 Published:2025-05-16

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摘要：

2024年以来,DeepSeek等生成式人工智能在俄语训练方面取得突破,为高校俄语教学的数智化转型提供了技术条件。本文以采用《走遍俄罗斯1》为教材的课程教学实践为例,探索“AI+HI”理念下大语言模型在高校俄语数智化教学中的应用路径和赋能方式。总体上看,大语言模型在高校俄语教学中的协同辅助具有多元化、多层次、多模态的应用特征,不仅能够实现学科知识图谱、能力图谱与问题图谱的个性化建模,也具备优化教学教案,辅助教学活动设计的技术潜力,可在课程宏观建构与教学微观设计中完成双重赋能。在秉持“以人为本”“以学为本”理念的良性人机互动中,大语言模型的介入有效提升了学生的俄语综合素质和跨文化交际能力,为中国青年讲好中国故事、登上国际舞台奠定了重要基础。

关键词: 大语言模型, 俄语教学, 数智化, 《走遍俄罗斯1》, AI+HI

Abstract:

Since 2024, generative artificial intelligence represented by DeepSeek has achieved breakthroughs in Russian language training, providing technical conditions for the digital-intelligent transformation of Russian language education in higher education. This study examines the teaching practice of a Russian language course employing The Way to Russia 1 as its core textbook, systematically exploring implementation pathways and enabling mechanisms of large language models (LLMs) in collegiate Russian instruction under the“AI+HI”framework. Comprehensive analysis reveals that LLM-assisted Russian language education demonstrates three distinctive operational characteristics: multidimensionality, stratification and modality integration. They not only enable personalized modeling of disciplinary knowledge graphs, competency graphs, and problem graphs, but also possess technical potential for optimizing teaching lesson plans and assisting instructional activity design, achieving dual empowerment in both macro-level curriculum construction and micro-level instructional design. Through positive human-machine interaction adhering to the principles of “people-oriented” and “learning-oriented”, the integration of LLMs has effectively enhanced students’ comprehensive Russian language proficiency and intercultural communication skills, laying a crucial foundation for Chinese youth to better tell Chinese stories on the international stage.

Key words: LLMs, Russian pedagogy, Digital and intelligentization, The Way to Russia 1, AI+HI

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