A Corpus-based Study On English Modal Sequences In Chinese College Students' Written Language

Modal verbs,as the main representation of modality,are an important grammar point in English writing for Chinese English learners.On the other hand,the polysemy and ambiguity of most English modal verbs have imposed difficulty of learning and appropriately using modal verbs for English learners.In the last decades,modal verbs have been investigated by linguists and scholars from different aspects.However,most of the previous studies focus only on the logic meanings and semantic characteristics of individual modal verbs,ignoring the research of modal verbs phrases or modal sequences.Thus,based on the Contrastive Interlanguage Analysis and corpus-driven approach and taking good use of advanced computer software tools,this thesis selects 1379 copies of Chinese college students' English compositions from TECCL as the research corpus and written texts from native speaker corpora LOCNESS and BNC as the reference corpus.The frequency distributions of modal verbs and modal sequences in two corpora have been investigated and compared,aiming to explore Chinese college students' using tendency and characteristics of modal verbs and modal sequences in their English writing.The following findings have been revealed from the results of corpus-based analysis and data statistics.Firstly,the frequency distribution of different modal verbs in Chinese English learners' writing is unbalanced.Compared with the native speaker corpus,Chinese college students significantly tend to overuse modal verbs can,should,will,ought to,need,must,shalland used to,while the modal verbs would,could and mightare underused by Chinese students;there is no significant difference in the frequency of modal verb may between two corpora.Secondly,Chinese college students are more likely to use such modal sequences as “modal verb + dynamic verb with unmarked tense or aspect” and “animate subject + modal verb” to convey deontic modality and less use modal sequences that typically express epistemic modal meanings.Moreover,Chinese students have the tendency to overuse verbs with unmarked tense and aspect after modal verbs or personal pronouns I,we,you,they,he/she before modals,avoiding those modal sequences such as “modal verb + verb with perfect aspect” or “the guide word of subject + modal verb” which are more complicated in grammar and semantics and with which they are not familiar.Lastly,the possible reasons for the discrepancy in using tendency of modal verbs and modal sequences between non-native corpus and native corpus are explored.Firstly,negative transfer of mother language leads to Chinese English learners to equate the meanings and using of English modal verbs with their translations in Chinese.Secondly,some English grammar books in China that are widely used by Chinese English learners influence their learning order and using frequency of different English modal verbs.Thirdly,learners' avoidance strategy makes students overuse certain modals and modal sequences that they are more familiar with and avoid some relatively more complicated modal sequences to reduce the chances of making mistakes.Finally,the culture and social value differences between China and western countries contribute to the differences in modality expressions.These research findings could shed light on the teaching and learning of English writing and the automated English essay scoring system.(1)Since the explanation of individual modal verbs are not helpful enough for modal verbs learning,the modal verbs should be interpreted and taught from the perspective of modal verb phrases or modal sequences.(2)The use of powerful computer software tools for corpus analysis enables teachers and students to find out more authentic language facts and which modals and modal sequences have been overused or underused by themselves,thus adjusting their writing accordingly and making their English writing be closer to the native speakers.(3)The using frequency and features of modals and modal sequences could be used as a variable,thus providing reference for the automated essay scoring system.