영어 학습자 코퍼스 기반 어휘다발의 구조적 패턴과 기능적 유형 분석
English Learner Corpus-based Analysis of Structural Patterns and Functional Types of Lexical Bundles
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초록
This corpus-based study is to analyze English lexical bundles in three learner corpora using Wordsmith 6.0. Specifically, this paper is to explore the frequency, structural patterns, and functional types of the extracted bundles in both native and non-native speakers’ English writing. To extract automatically the most frequent 4-word lexical bundles from the corpora, the cluster program was utilized. The results showed that 1) in terms of frequency, non-native speakers used prompt bundles repeatedly other than native speakers; 2) native and non-native speakers’ use of structural patterns was remarkably different; 3) from the perspective of functional types, non-native speakers used more stance bundles than native speakers did. Pedagogical implications and limitations of the study were provided. More research about lexical bundles are required for deeper analysis of native and non-native English learner corpus and English variety.
Abstract
This corpus-based study is to analyze English lexical bundles in three learner corpora using Wordsmith 6.0. Specifically, this paper is to explore the frequency, structural patterns, and functional types of the extracted bundles in both native and non-native speakers’ English writing. To extract automatically the most frequent 4-word lexical bundles from the corpora, the cluster program was utilized. The results showed that 1) in terms of frequency, non-native speakers used prompt bundles repeatedly other than native speakers; 2) native and non-native speakers’ use of structural patterns was remarkably different; 3) from the perspective of functional types, non-native speakers used more stance bundles than native speakers did. Pedagogical implications and limitations of the study were provided. More research about lexical bundles are required for deeper analysis of native and non-native English learner corpus and English variety.
참고문헌 (33)
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