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摘要不赞同言语行为是表达不同意见的一种面子威胁言语行为，说话者需要采取各种缓和策略减少面子威胁。本文在Brown和Levinson的礼貌理论以及言语行为理论的框架下，参照Rees-Miller对不赞同言语行为的分类，研究我国英语专业研究生在学术语境下如何表达不赞同意见。本研究以南京理工大学英语专业研究生课堂内外的讨论为语料，分析其中的78个不赞同言语行为，探讨学习者使用的语用策略及其影响因素。研究发现：英语学习者在表达不赞同时使用缓和策略最多，尤其是消极礼貌策略，使用强化不赞同最少。究其原因，可能有：传统文化、社交距离、权利关系和说话习惯等因素的影响。学习者学术不赞同言语行为的表现从一定程度上反映出学生在学术语境下的外语语用能力。28927
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关键词 不赞同言语行为 面子威胁 学术语境 语用能力
毕业论文外文摘要
Title A Study on EFL Learners’ Academic Disagreement in Universities of Science and Technology—— A Case Study of Students from NJUST
Abstract
Disagreement is a face-threat act that expresses different or opposing views, which speakers try to avoid or mitigate by all means. This paper investigates strategies Chinese EFL learners of English major use to express academic disagreement under the framework of Brown and Levinson’s Politeness Theory and Speech Act Theory. According to Rees-Miller’s classification of disagreement, the research is aimed to analyze disagreement strategies and relevant factors in the 78 disagreement act identified from class discussions and office seminars of post-graduate students of English major from Nanjing University of Science and Technology. It is found that EFL learners tend to use softened strategy most, especially the negative politeness strategy, and aggravated strategy least, which is probably caused by traditional culture, social distance, relative power and speaking habit. The disagreement strategies students choose, to some extent, reflect their foreign language pragmatic competence in academic context.
Keywords disagreement face threat academic context pragmatic competence
Table of Contents
1 Introduction 1
1.1 Research Background 1
1.2 Research Object 1
1.3 Layout of the Thesis 2
2 Literature Review 2
2.1 Definition of Disagreement 2
2.2 Studies on Disagreement and Politeness 3
2.3 Studies on EFL Learners' Pragmatic Competence 4
2.4 Achievements and Shortcomings 5
3 Theoretical Framework 5
3.1 Austin's Speech Act Theory 5
3.2 Brown & Levinson's Politeness Theory 6
3.3 Summary 8
4 Methodology 8
4.1 Research Questions 8
4.2 Data Collection 9
4.3 Coding Scheme 9
4.4 Data Analysis 10