词汇
语言学
心理学
自然语言处理
计算机科学
哲学
作者
David D. Qian,Linda H. F. Lin
出处
期刊:Routledge eBooks
[Informa]
日期:2019-07-30
卷期号:: 66-80
被引量:54
标识
DOI:10.4324/9780429291586-5
摘要
The last 30 years or so have witnessed the flourishing of much scholarly work on the association between learners’ vocabulary knowledge and their language proficiency. A large majority of these studies targeted EFL (English as a foreign language) or ESL (English as a second language) learners. In spite of the differences in levels of association, these studies have generally found that learners’ vocabulary knowledge is by and large associated with their language proficiency. Some research has also looked into the relationship between learner’s vocabulary knowledge and their academic achievements and a significant positive relationship has been identified.
Notwithstanding the general association between vocabulary knowledge and language proficiency, ESL learners’ depth of vocabulary knowledge has been found to be able to better predict some of the four macro language skills than their vocabulary size. The differences between these two facets of vocabulary knowledge have given rise to the prevalence of research into the relationship between learners’ vocabulary knowledge and their proficiency in reading and listening, but relatively fewer studies on the relationship between vocabulary knowledge and writing and speaking. Drawing on the main studies in the field, this chapter examines the research literature in the following three areas: first, the differences in vocabulary size and depth of knowledge in predicting the four macro language skills; second, the vocabulary size and lexical thresholds that different learners need to achieve in order to be able to effectively process written and spoken language data, or to successfully manage different levels of reading and listening tasks; third, measures for examining lexical richness (e.g., lexical frequency profile, lexical sophistication, and lexical variation) in learners’ writing. Based on a critical review of the relevant literature, the chapter will also identify important research issues in this area and suggest desirable directions for future research.
科研通智能强力驱动
Strongly Powered by AbleSci AI