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

doi:10.12339/j.issn.1673-8578.2025.01.015

Abstract

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

LU Huaguo. Design of Data-Driven Teaching of Noun Terms: Categorizing, Extracting and Applying Terminological Knowledge[J]. China Terminology, 2025, 27(1): 94-101.

Figures/Tables 3

References 19

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