中国科技术语 ›› 2025, Vol. 27 ›› Issue (1): 94-101.doi: 10.12339/j.issn.1673-8578.2025.01.015

• 数据挖掘 • 上一篇    下一篇

英语名词术语数据驱动教学设计:术语知识解析、提取和应用

卢华国()   

  1. 南京理工大学外国语学院,江苏南京 210094
  • 收稿日期:2024-05-27 修回日期:2024-08-21 出版日期:2025-01-07 发布日期:2025-01-07
  • 作者简介:

    卢华国(1979—),南京理工大学外国语学院教授,硕士生导师;中国辞书学会理事和双语词典专业委员会常务理事。研究方向为术语翻译、词典学、认知语义学和语料库语言学。通信方式:

  • 基金资助:
    2021年度国家社会科学基金后期资助一般项目“英汉专科学习型词典语境化设计研究”(21FYYB004)

Design of Data-Driven Teaching of Noun Terms: Categorizing, Extracting and Applying Terminological Knowledge

LU Huaguo()   

  • Received:2024-05-27 Revised:2024-08-21 Online:2025-01-07 Published:2025-01-07

摘要:

名词术语在专业交际中发挥了重要作用,但是由于其承载了丰富的专业知识,给专门用途英语教学设计带来了挑战,教师对英语名词术语教学中应该教传授什么知识及如何获取相关知识都感到困惑。文章提出了针对英语名词术语的数据驱动教学设计,即借鉴生成词库理论提出的物性结构把名词术语知识分为概念关系和搭配关系,使用Sketch Engine快速创建面向术语教学的语料库,精选包含前述两类知识的索引行,基于索引行编写四种词汇练习。文章提出的数据驱动教学设计为解决当前专门用途英语教学中存在的问题带来了新启示。

关键词: 物性结构, 名词术语知识, 数据驱动教学, 专门用途英语教学, Sketch Engine

Abstract:

Noun terms play an important role in specialized communication. The specialized knowledge they carry poses challenges to the teaching of English for specific purposes (ESP): teachers often feel at a loss about what to teach regarding these terms and how to teach it. In response to these problems, this paper draws upon the Qualia Structure (QS) proposed in the theory of Generative Lexicon and classifies the specialized knowledge of noun terms into conceptual relations and collocational relations. This paper also uses Sketch Engine (SkE) to build instant specialized corpora, select knowledge-rich contexts, and create four types of vocabulary exercises. It is believed that the proposed design of data-driven teaching of noun terms provides insights into solving the aforementioned problems.

Key words: qualia structure, knowledge of noun terms, data-driven teaching, ESP teaching, Sketch Engine