| This Paper presents a contrastive study on adverbial connectors in the English writings written by the native English students and the students in Gansu Agriculture University (GSAU). Based on the research, the study explores the following questions:First, do Chinese college students use adverbial connectors to the same extent compared to the native students in frequency?Second, do students in GSAU tend to overuse some certain adverbial connectors.Third, what are the specific characteristics of adverbial connectors used in students’writings in GSAU?In order to answer above questions, this research adopts the methodology of Contrastive Interlanguage Analysis (CIA) and corpus-based analysis by using two corpora sources:LEWC(Learner of Gansu agriculture university English Writing Corpus) and BAWE (British Academic Written English). Between these two corpora, LEWC is a self-established Learners’corpus, and BAWE is the native-speaker corpus. By using the concordance tools AntConc3.2.3, the author obtains data of frequencies, standard frequency and the position distribution of adverbial connectors, etc. which were collected in the above two corpora to compare the adverbial connectors used in the students’writings in GSAU with native students’. The major findings of the study include:1. The students in GSAU tend to overuse adverbial connectors in their writings in contrast to English native students. Besides, students in GSAU also underuse some certain ones. 2. After counting all the91adverbial connectors in7semantic types and calculating the percentage of each semantic type holds in both two corpora, we find the types of additive, result/inference and contrast/concession rank in the first three places firmly in both observed and reference corpora. And we also observe the STD Frequency of top ten adverbial connectors of additive in LEWC and BAWE, then, we find that among the top10adverbial connectors, the words which indicate the meaning of listing, just like, first(ly), second(ly) and third(ly) account for almost three to fifth. While in BAWE, the listing adverbial connectors are first and second and only occupy very little part in it.3. With the comparison of the top twenty adverbial connectors in the two corpora, we find that the number of top20adverbial connectors used most frequently in the two corpora takes the large parts of the total quantity of adverbial connectors. The percentage is86.73%and81.90%, respectively. The most popular used one in LEWC is so, while in BAWE, students prefer to use also very much. Besides, in the LEWC corpus, there are11words belonging to additive adverbial connectors, taking more than a half of20s, while in BAWE, there are just6belong to that semantic type, taking about one quarter of20s.4. While we investigate the clause-position of the adverbial connectors used in the two corpora, we find clause-initial position is the most popular position for adverbial connectors in LEWC with55.45per cent, while English native students prefer to put the adverbial connectors in the medial position. The high per cent of71.94%clearly proved it. 5. Retrieving in the two sub-corpora which set up based on the score of the writing in LEWC, we find there do have some clear-cut differences between them. Rather, such differences seem to imply that the students of high English proficiency are more cautious with the appropriate usage of adverbial connectors. And they do have the tendency to use them in the more extensive range.Accordingly, author attributes those problems to the following sources:LI transfer, instruction from writing handbooks and teachers, learners’lack of stylistic awareness, learners’lack of full understanding of some adverbial connectors, the misconception about the use of connectors the learners hold, etc. The author also gives some pedagogical implications based on the research.The study intends to shed light on the characteristic of students’use of adverbial connectors in LEWC to help raise both teachers’and learners’awareness of the value of adverbial connectors in English writing. |
PDF Full Text Request