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An Analysis Based On HSK Dynamic Composition Corpus On Errors About Learning Verb-object LIHECI

Posted on:2013-04-05Degree:MasterType:Thesis
Country:ChinaCandidate:M N LiuFull Text:PDF
GTID:2235330374461249Subject:Foreign Linguistics and Applied Linguistics
Abstract/Summary:PDF Full Text Request
Verb-object LIHECI is the most complex and the largest number of Chinese LIHECI in modern Chinese. The combination of verb-object LIHECI can use as a general verb only. It also can be restricted by adverbs of degree. The isolation of Verb-object LIHECI can be expanded. For foreign students, learning Verb-object LIHECI is hard and important. Verb-object LIHECI learning focus is not on its meaning and nature, but rather how to use, especially the expansion of Verb-object LIHECI. The method of Verb-object LIHECI expansion is a bottleneck of Chinese learning.The corpus is from HSK Dynamic Composition Corpus which collected the composition of students in Beijing Language and Culture University. The author collected and collated the errors of Verb-object LIHECI, and then analyzed the errors and gave some advices.There are six chapters in the paper.The first chapter introduces the topics of significance, motivation, study, research methods, and Research.The second chapter, there are an overview of Verb-object LIHECI, classification and Verb-object LIHECI expansion.The third chapter, the main corpus collected to classify and analyze error sentence at a syntactical level.The fourth chapter explores the underlying errors.The fifth chapter according to the reason of errors gives the recommendations of the teaching and learning.The sixth chapter the main features and shortcomings of this study are described.The corpus is from HSK Dynamic Composition Corpus. This way can avoid the human induced factors. It is more realistic and objective to describe the using condition of Verb-object LIHECI. At last, the author hope that the paper will provide more evidence to study in future.
Keywords/Search Tags:HSK Dynamic Composition Corpus, verb-object LIHECI, error analysis
PDF Full Text Request
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