A Study On The Acquisition Of Chinese Verbs In Chinese Language

Chinese Speech Act Verbs (SAVs) can be divided into bivalent SAVs and trivalent SAVs. According to their selections of preposition structures, SAVs can also be divided into two parts, which are the verbs that must/could use a preposition to introduce their dative role and the verbs that never use it. The prepositions they often use are "Dui(对)", "Xiang(向)"Gei(给)"He(�'�), "Gen(跟)". From the view of the function of SAVs, Chinese SAVs can be divided into unidirectional SAVs and interactive SAVs. Unidirectional SAVs have eight secondary categories, while interactive SAVs have two. They can be further classified into 27 subclasses.The study found acquisition of SAVs improves a lot when study goes further. There are still four types of errors, which are omission, addition, ill-ordering and overrepresentation. On the basis of analysis, errors become much more difficult as the grade becomes higher. There are four main features of errors. ①Overrepresentation of verbs is the main type of errors. ②Foreign students with different mother languages share the generality on error types. ③Central words of verbs’ overrepresentation are usually frequently used words in Chinese.④Error rate appears the development trend of U-shaped.There are four main reasons for students to produce these errors. ①The close meanings and usages result in confusion and misusing. ②During the study, the use mother or medium language is unavoidable, while the translations in textbooks or reference books are not clear enough. ③The misleading of learning strategies may cause overgeneralization in the meanings or usages of some SAVs. According to the features and reasons of these errors, a correct view on vocabulary acquisition should be established. More Chinese interpretations and comparison between SAVs should be available in textbooks. By creating communication context, teachers can enlighten students to find out the differences between SAVs. Meanwhile, chunk teaching can be used for reference, with which retrieval speed of language units can be improved.