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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.1
- 수록면
- 37 - 52 (16page)
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This study explores whether linguistic features can predict second language writing proficiency in the Michigan English Language Assessment Battery (MELAB) writing tasks. Advanced computational tools were used to automatically assess linguistic features related to lexical sophistication, syntactic complexity, cohesion, and text structure of writing samples graded by expert raters. The findings of this study show that an analysis of linguistic features can be used to significantly predict human judgments of the essays for the MELAB writing tasks. Furthermore, the findings indicate the relative contribution of a range of linguistic features in MELAB essays to overall second language (L2) writing proficiency scores. For instance, linguistic features associated with text length and lexical sophistication were found to be more predictive of writing quality in MELAB than those associated with cohesion and syntactic complexity. This study has important implications for defining writing proficiency at different levels of achievement in L2 academic writing as well as improving the current MELAB rating scale and rater training practices. Directions for future research are also discussed.
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참고문헌 (35)
참고문헌 신청
Baayen, R. H. / 1993 / The CELEX lexical database (CD ROM)ROM) / Linguistic Data Consortium
Barkaoui, K. / 2007 / Teaching writing to second language learners : Insights from theory and research :35~48
Brill, E. / 1995 / Transformation based error driven learning and natural language processing : A case study in part of speech tagging / Computational Linguisti cs 21:543~565
BNC XML / British National Corpus, version 3
Brown, G. D. A. / 1984 / A frequency count of 190,000 words in the London Lund Corpus of English Conversation / Behavior Research Methods, Instrumentation & Computers 16:502~532
Barkaoui, K. / 2007 / Teaching writing to second language learners : Insights from theory and research :35~48
Brill, E. / 1995 / Transformation based error driven learning and natural language processing : A case study in part of speech tagging / Computational Linguisti cs 21:543~565
BNC XML / British National Corpus, version 3
Brown, G. D. A. / 1984 / A frequency count of 190,000 words in the London Lund Corpus of English Conversation / Behavior Research Methods, Instrumentation & Computers 16:502~532
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