基于语料库的反馈在学术写作教学中的研究

1、基于语料库的反馈在学术写作教学中的研究基于语料库的反馈在学术写作教学中的研究Study on Corpus-Based Feedback in Teaching of Academic English Writing 2141020008 高晓娜高晓娜 Outlinev1.Introduction v2.Literature Reviewv3.Research Methodology 3.1 Research questions 3.2 Research design 3.3 Research procedure 3.4 Data analysis processv4.Data Analysi

2、s and Discussion 4.1 Quantitative analysis 4.2 Qualitative analysisv5.Conclusion 1.Introduction vPublish or perish is a vivid and real stiuation which cannot be ignored for Chinese academic workers.Numerous Chinese those scholars have submitted their paper to international journals,but many have bee

3、n rejected and criticized by those academic journals due to language problems.Therefore,academic English writing training is necessary for postgraguate students if they want to practice the academic working in the future.vHowever,in the writing teaching there are many practical difficulties.postgrad

4、uate academic writing course is still textbook-based for some reasons, but many textbooks or writing manuals can only provide general writing guidance rather than individual and discipline-oriented suggestions.teachers are mostly graduated from the disciplines as English Language or literature which

5、focus on language and literature with little scientific training and content knowledge, therefore they may not be qualified enough in teaching content-based or discipline-oriented research article writing.the size of writing class is usually so big that it is difficult to meet the individual needs o

6、f students. v vTherefore,information technology assisting language learning is a tendency and an opportunity.Corpus-based language learning actually gives students an opportunity to discover learning and corpus linguistics is useful and proper for postgraduate English writing teaching in Chinese uni

7、versities.vResearch purposes vto explore the discrepancy between Chinese students and native writers in academic English writing, to explore the application of corpus-based approach in academic English writing course. On the basis of the research, we hope to help the academic English writing teacher

8、s to improve their teaching and to stimulate students academic language awareness and to empower them in the participation of academic community communication confidently. vResearch significancesvThe research uses corpus-based resources in class which could provide opportunities for students to expl

9、ore and find the language pattern on their own. vIn this study, one application of computer, corpus-based approach,in the writing course could provide chances for teachers to do preparation for the coming challenges.vFor the discipline,the combination of discourse analysis and corpus linguistics in

10、the academic writing teaching could offer a new perspective for the writing teaching practice.v2.Literature ReviewvAcademic writig teachingvWritting as a process:feedbackvWriting as a genre:Problem-Solution patternvWriting as a product:corpus-based analysis3.Research MethodologyvThis empirical study

11、 adopted a mixed methodology with quantitative analysis on the basis of corpus linguistics approaches and qualitative analysis on open survey questionnaires.Corpus-based feedback was introduced into the writing classroom.v3.1 Research questionsv1.What are language differences between Chinese postgra

12、duate students and native speakers in academic English discourse? Whether did Chinese students master the lexical signals for the Problem-Solution Pattern?v2.What changes occurred after the corpus-based feedback was introduced in the academic English writing class?v3.How did students attitude change

13、 after the corpus-based feedback was introduced? v3.2 Research designv(1)ParticipantsvThe participants were non-English major postgraduates (n=205) who came from 5 disciplines (12 professional directions) (see Table 3-1). Among them, 40% students came from humanities directions,while other 60% came

14、from science and engineering directions.Of these 205 students, 74 are female and 131 male. Most of them have been learning English formally more than 12 years (3 years in primary school,6 years in middle school, 2 years in the first 2 years of college and 1 year for test preparation) v(2)Toolsv the

15、WordSmith Tools 5.0 (Scott 2010) including 3 main modules: WordList, Concord, and Key Wordsv(3)Other instrumentsvtwo survey questionnaires were conducted before and after the teaching experiment v3.3 Research procedurev(1)In the Preparation stagevi.Two reference corpora were vselected:the BNC and th

16、e BAWE.vii.Two research foci were determined va. interlanguage phenomena; vb. lexical signals for Problem-Solution Pattern; vc.a revised teaching plan with feedback which was the center of the research was designed.vd.technical details were specified, including participants selection, writing assign

17、ment topics and genre,experiment organization, submission procedure and details(plain text files via email), and questions for exploring attitudes of students.v(2)In the experiment stage:vThere were only 6 sessions of writing course in the semester therefore students were required to write 5 composi

18、tions and I gave 5 feedbacks on the basis of corpus analysis. The process could be seen in Figure 3-2. v(3) Feedback stage:vIn the following teaching sessions, each 2-hour class was divided into two parts:30-minute feedback based on the corpus-based analysis data which drew from the collection of pr

19、evious homework and 90-minute writing teaching which followed the original schedule.v(4) In the last session:vstudents were required to write a reflection on the whole teaching, especially their views on the corpus-based feedback in the last session.vFinally, all compositions were compiled into 5 su

20、b corpora as quantitative data.v3.4 Data analysis processvThe data analysis included two parts: quantitative and qualitative (Figure 3-3). The quantitative analysis consisted of two contrast analyses. vThe first one would be conducted between two corpora: the learner writing corpus (LWC), compiled b

21、y the researcher and the BAWE, used as the reference corpus. The second could be called dynamic analysis to study the development of the students by 5 sub-corpora (5-session writing assignments).4.Data Analysis and Discussionv4.1 Quantitative analysisv4.1.1 Contrast between the LWC and the BAWEvA. B

22、asic statisticsvTable 4-1 gives basic statistics of the LWC and the BAWE which were achieved by WordSmith Tools 5.0. vB. Frequency analysisv(1) Personal pronounsvThe frequency details across two corpora can be seen in Figure 4-2. (1) Chinese students use WE and YOU much higher than the British stude

23、nts. (2) For I and THEY,no big difference occurs between Chinese and English students. (3) Third person pronouns, HE and SHE,British students use them more frequently. va. WEvFirst, through Concord module of WordSmith Tools, the collocations of WE are showed in the Figure 4-3 vThen To further calcul

24、ate the collocation capability, we used T Score to order the words again. Figure 4-4 shows the 30 biggest T Score of the collocation words in two corpora. some differences appear between the two corpora: (1) T Scores of SHOULD and ALL with WE in the LWC are much higher than that in the BAWE. vThe fi

25、gure demonstrates that WE ALL KNOW is likely to occur in the first half of the texts, which matches with the position of Situation of Problem-Solution pattern. Chinese students like to use WE ALL KNOW, or AS WE ALL KNOW to explain the pervasiveness and seriousness of the problems.vthe problems. v In

26、 the same way, the plot graph shows a very interesting tendency-that WE SHOULD occurs more frequently in the last half part of the texts (Figure 4-5). According to Problem-Solution pattern,the last half of the writing should be the solution suggestions. The plot indicates that Chinese students like

27、to use WE SHOULD to introduce possible solutions for problem. v(2) Modal verbsvFigure 4-8 (1) Frequencies of the most common modal words used by British students are quite balanced,except MIGHT and SHALL(2)Chinese students use some model verbs much more frequently. vC. Discourse featuresvThe wordlis

28、t and keywords procedure have been used to discover discourse features.vFigure 4-12 illustrates the most frequent words which signify the Problem element of the Problem-Solution pattern. Chinese students used those words far more than British students.PROBLEM/S were explicitly used to identify the P

29、roblem. vD. Other overused words v4.1.2. Contrast among the sub-corpora of the LWCvA. Basic statisticsvIn sum,file size,total tokens and types increased .vB. Linguistic featuresvFrom the wordlists of the 5 sub-corpora,They changed from one extreme end to the other from underuse to overuse of THE and

30、 from overuse to less overuse of WE vC. Signals for Problem-Solution patternvThe teacher explicitly gave the instruction of lexis-discourse relationship: lexical signals for Problem-Solution pattern. vIt reflected the teaching content and the lexical features of Problem-Solution Pattern.in the fourt

31、h assignment, we found the dramatic drop of all signals of Solution element. After checking the topic of the compositions, we found that it was The impact of the Smart Phone on interpersonal communication, which was the only assignment which we did not give the obvious hints of Problem-Solution Patt

32、ern like other 4 assignments.v4.2. Qualitative analysisv Survey QuestionnairesvAttitude variationv(1)In the answer to the survey questions in the first session, students comments on the expectation of the writing course were more general and vague.In the last session,they give more vspecific descrip

33、tions on the academic English writing.v(2)In terms of their understanding of academic English writing,In the initial understanding of the first session,the students used adjectives like professional, exact,clear,advanced, complicated, written,and academic to modify the academic English writing,in th

34、e comments of the last session, most students could give details on the academic English writing. They mentioned the differences explicitly and even gave examples such as HOWEVER and THE.v(3) On the homework and the feedback,most students expressed that they enjoyed the form of teaching. Some said t

35、he data and the figures made easy to understand.v5.Conclusionv5.1. FindingsvQuantitative analysis vThe results showed: (1)There are differences between Chinese students and British students in terms of use of articles,personal pronouns, modal verbs, adjectives, nouns,etc. (2) Students already master

36、ed some signals for Problem-Solution Pattern writing,but the types and flexibility were restricted.If the researcher found an underuse word and showed it to the students on the feedback period in the classroom,a dramatic increase of the use of the word could be found in the next assignment. But in t

37、he following assignments,we could watch a slow opposite tendency from the data. The overuse situation was just the opposite.vQualitative datavA majority of students found it new and effective to use corpus-based feedback in the writing course. Most students noticed the differences between their own

38、writing with that of native speakers and were enthusiastic about working with the corpus and agreed that the corpus-based analysis helped them improve their writing and intended to learn it more in futuree.vc v5.2. Limitationsv(1)The biggest weakness is coverage of the study. We analyze only several

39、 categories, such as subject pronouns,modal verbs, adjectives,linking words,and some abnormal words.v(2)The focus was on the overuse,misuse,and underuse of the learners language practice,which might reduce the value of contrast study and simplify the evaluation of the results. v(3)Due to limited time and human power, the sample selection was restricted in terms of number and sampling procedure.v5.3. Sugges