Improving Incidental L2 Vocabulary Learning With Latent Semantic Analysis

DOI
  • HAMADA Akira
    Graduate School, University of Tsukuba:The Japan Society for the Promotion of Science

Bibliographic Information

Other Title
  • 潜在意味解析を用いた付随的語彙学習の成果向上

Description

This study examined whether word-context semantic similarity computed by Latent Semantic Analysis (LSA) predicts the performance of incidental L2 vocabulary learning. LSA is relevant to the usage-based model of language learning, which premises that learners obtain lexical knowledge from the information about how words are used in context. In the experiment, 153 Japanese undergraduates were given 20 target words with contexts whose proposition had higher or lower semantic similarity to those words (HSS vs. LSS context) in the lexical inference and multiple-choice glosses tasks. A Vocabulary Knowledge Scale (VKS) test was used to assess incidental gains in word meaning and usage knowledge. The analyses of the task performances showed that the learners inferred the target word meanings from the HSS contexts more successfully than from the LSS ones, but obtained similar scores between the two context conditions in the multiple-choice glosses task. Nevertheless, the VKS results demonstrated that the HSS contexts greatly contributed to the incidental gains in word meaning and usage knowledge. Thus, LSA predicted the outcomes of incidental vocabulary learning, which indicates that the learners acquired lexical knowledge from usage-based contextual information.

Journal

Details 詳細情報について

  • CRID
    1390282680799865728
  • NII Article ID
    110010006581
  • DOI
    10.20581/arele.26.0_61
  • ISSN
    24320412
    13448560
  • Text Lang
    en
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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