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<p>Vocabulary acquisition has always been a core issue and challenge in teaching Chinese as a foreign language. This paper constructs a Chinese word-formation complex network based on the syllabus vocabulary of the <i>Chinese Proficiency Grading Standards for International Chinese Language Education</i> and employs the k-core decomposition method to identify a subset of Chinese characters with the robust word-formation capabilities. Using the “proficiency level” from <i>The Chinese Proficiency Grading Standards for International Chinese Language Education</i> as a reference for the learnability of vocabulary and characters, we explore the relationship between characters’ word-formation capabilities and their learnability. We find that the vast majority of characters with robust word-formation capabilities are labeled as lower “proficiency levels,” indicating that these words are easier for learners to master. Previous studies suggest that focusing on high-frequency word-formation components (such as roots in certain languages) facilitates the acquisition of new words. We propose that this complex network-based word-formation analysis method can, under the constraint of limited corpus resources, efficiently identify characters with robust word-formation capabilities. This provides valuable insights for developing vocabulary lists for Chinese language teaching, enabling learners to prioritize easily acquired characters with strong word-formation capabilities, thereby reducing their learning burden.</p>

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Variations in Chinese Vocabulary Networks across Different Proficiency Levels and Their Implications for Teaching Chinese as a Second Language

  • 期刊论文

  • 发表日期：

    2025年10月1日

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  • Kexin Yang,
  • Huibin Zhuang

摘要

Vocabulary acquisition has always been a core issue and challenge in teaching Chinese as a foreign language. This paper constructs a Chinese word-formation complex network based on the syllabus vocabulary of the Chinese Proficiency Grading Standards for International Chinese Language Education and employs the k-core decomposition method to identify a subset of Chinese characters with the robust word-formation capabilities. Using the “proficiency level” from The Chinese Proficiency Grading Standards for International Chinese Language Education as a reference for the learnability of vocabulary and characters, we explore the relationship between characters’ word-formation capabilities and their learnability. We find that the vast majority of characters with robust word-formation capabilities are labeled as lower “proficiency levels,” indicating that these words are easier for learners to master. Previous studies suggest that focusing on high-frequency word-formation components (such as roots in certain languages) facilitates the acquisition of new words. We propose that this complex network-based word-formation analysis method can, under the constraint of limited corpus resources, efficiently identify characters with robust word-formation capabilities. This provides valuable insights for developing vocabulary lists for Chinese language teaching, enabling learners to prioritize easily acquired characters with strong word-formation capabilities, thereby reducing their learning burden.