本文選題：高級階段留學(xué)生 + 漢語書面表達(dá)　； 參考：《上海外國語大學(xué)》2017年碩士論文

【摘要】：結(jié)合目前第二語言學(xué)習(xí)領(lǐng)域作文評判的成果和個(gè)人寫作教學(xué)實(shí)踐經(jīng)驗(yàn),我們發(fā)現(xiàn):處于不同分?jǐn)?shù)段的作文,在詞匯難度、平均句長等淺層文本特征上存在差異。這些特征可用量化的方法進(jìn)行統(tǒng)計(jì),本文稱其為客觀性因素。本文以此著手,首先運(yùn)用相關(guān)分析的方法來探討這些客觀性因素和其所在文本分?jǐn)?shù)是否成正比或反比,以及客觀性因素在不同等級作文上的分布差異;之后通過回歸分析建立的評分模型獲得對人工評分有顯著影響的客觀性因素并檢驗(yàn)該模型預(yù)測分?jǐn)?shù)的信度;最后基于結(jié)論對評分標(biāo)準(zhǔn)、評分方法、寫作教學(xué)及教材編寫提出了建議。本論文共分五章:第一章緒論;本文首先敘述了論文的選題緣由和研究對象,然后進(jìn)行了針對作文評分影響因素和客觀化評分的文獻(xiàn)回顧并對其進(jìn)行了總結(jié),之后說明了研究的目的和意義,最后闡明本文研究思路和運(yùn)用的數(shù)據(jù)處理方法。第二章客觀性因素和人工評分關(guān)系研究實(shí)施;在實(shí)驗(yàn)之前,我們通過匯總前人研究中選取的文本特征,獲得對各客觀成分的研究頻率,并結(jié)合前人的研究結(jié)論,共選取了20個(gè)客觀性因素;在學(xué)習(xí)了HSK作文評分標(biāo)準(zhǔn)和《歐洲語言共同參考框架:學(xué)習(xí)、教學(xué)、評估》(以下簡稱《框架》)中的語言能力量表等之后,我們制定了用于本次研究的整體量表,并在試評后作出更改,最后用于作文測評。此外,我們對文本來源、評分員信息及樣本分析方法也進(jìn)行了說明。第三章SPSS處理客觀性因素和人工評分結(jié)果及分析;首先我們整理了研究語料,依據(jù)樣本分?jǐn)?shù)對文本進(jìn)行了分檔,然后在各檔中隨機(jī)抽取一篇用于試評,在評分員對樣本語言質(zhì)量有一定認(rèn)識后開始正式測評。評分時(shí)我們選用整體量表獲得作文總分,并依據(jù)得分將作文分成三檔,隨后我們統(tǒng)計(jì)了各檔中的客觀性因素,并分析了這些因素的數(shù)據(jù)是否與得分成正比或反比,即兩者是否具有相關(guān)關(guān)系。為了更詳細(xì)地說明客觀性因素與總分的關(guān)系,我們將樣本中的客觀性因素和對應(yīng)總分進(jìn)行回歸分析,獲得對總分有有效解釋力的顯著因素,并隨機(jī)選取樣本人工再測,將所得分?jǐn)?shù)與用回歸方程得到的分?jǐn)?shù)進(jìn)行T檢驗(yàn)以驗(yàn)證回歸方程的預(yù)測信度。第四章評分建議;在測評中,我們獲得了對總分有顯著影響的客觀性因素,我們認(rèn)為這些因素應(yīng)納入評分標(biāo)準(zhǔn)中;此外,我們也分析了評分員對不同檔次文本的嚴(yán)厲度和評分員之間的一致性程度,同時(shí)考慮了顯著影響評分員的因素,對評分方法提出了建議。第五章結(jié)語;本次研究結(jié)論分為兩部分。一是得出客觀性因素與總分之間的關(guān)系,具體為作文分?jǐn)?shù)越高,非常用詞比重越高,錯(cuò)字?jǐn)?shù)、錯(cuò)詞數(shù)和錯(cuò)句數(shù)越少,總句數(shù)、分句數(shù)越多,平均分句長、平均句長等越長。二是得到對評分有顯著影響的因素。在低檔是詞匯難度,中檔是詞匯難度和文章流利度,高檔是詞匯難度、文章長度和文章正確度。在后續(xù)的研究中,我們認(rèn)為可以增加研究樣本,采用評分專家進(jìn)行評分,以改善實(shí)驗(yàn)。
[Abstract]:Combining the second language learning achievement and personal evaluation of composition writing teaching practice experience, we find that in different levels of composition in lexical difficulty, average sentence length and other characteristics of the text of shallow differences. These features can be quantified by statistics, the paper called for objectivity factors. This method to we use correlation analysis to explore these factors and objectivity of the text is proportional to the fraction or inverse, distribution in different levels on the composition and objective factors; the objective factors have significant influence on artificial scoring score model regression analysis to establish the prediction model and test the reliability of scores; finally, based on the conclusion the scoring method of standard for evaluation, writing, teaching and textbook compiling suggestions. This paper is divided into five chapters: the first chapter is the introduction firstly; Describes the researchbackground and object, then according to the grading factors and objective scoring of the literature was reviewed and summarized them, then explains the purpose and significance of the research, finally expounds the idea and method of data processing in this paper. The second chapter study on the relationship between artificial factors and objective scores; before the experiment, we through the summary of text feature selection in previous studies, research on the frequency of each objective component, combined with the previous research conclusions, we select 20 objective factors; in the study of the composition of HSK standard for evaluation and "common European Framework of reference for languages: learning, teaching, assessment (hereinafter referred to as < > after the framework >) language ability scale, we developed for the overall volume of the study table, and make changes in the assessment test, finally used for writing assessment. In addition, we in this paper The source of information, rater and sample analysis method is also described. The third chapter SPSS objective factors and artificial scoring results and analysis; first we analyzed the research data, according to the sample scores were classified to the text in the file, then randomly selected for a trial evaluation, began formal evaluation in the score who have some knowledge of quality. After the sample language score when we choose the whole scale to obtain composition scores, and scores according to the composition into third gear, then we counted each file in the objective factors, and analyzed the data for these factors are directly proportional or inversely with scores, which both are related to more. A detailed description of the relationship between the objective factor and the total score, we will be in a sample of objective factors and the corresponding score regression analysis, get effective explanation to the total score of the significant factors, and with the The sample machine manual test, the scores and scores of the regression equation to predict the reliability of T test of the regression equation. The fourth chapter score recommendations; in the evaluation, we obtain objective factors have significant influence on the total score, we believe that these factors should be included in the standard for evaluation; in addition, we also analyze between raters for different grades of the text of the severity and rater consistency at the same time, considering the significant influence factors of raters, suggestions on scoring method is proposed. The fifth chapter is the conclusion; the conclusion of the study is divided into two parts. One is the relationship between the objective factors and the total score, the writing scores for specific the higher, the higher the proportion of words is very wrong, wrong words, words and sentences are few, the total number of sentences, clauses number, average clause length, average sentence length and longer. Two is obtained had a significant effect on the score for Low grade is lexical difficulty. Middle grade is lexical difficulty and article fluency. High-end is lexical difficulty, article length and article accuracy. In subsequent research, we think that we can increase research samples and score experts to score, so as to improve the experiment.

【學(xué)位授予單位】：上海外國語大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：H195

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李麗;;英語寫作評分中的評分員效應(yīng)研究[J];開封教育學(xué)院學(xué)報(bào);2016年05期

2 陳建林;;高風(fēng)險(xiǎn)英語考試作文評分員社會心理因素研究[J];外語教學(xué)理論與實(shí)踐;2016年01期

3 陳建林;朱欣君;;寫作能力行為測試評分員培訓(xùn)研究述評[J];外國語文研究;2016年01期

4 左映娟;馮蕾;;大學(xué)英語寫作的評分標(biāo)準(zhǔn)維度研究——基于Writingroadmap和批改網(wǎng)的評分對比[J];現(xiàn)代教育技術(shù);2015年08期

5 張文星;鄒申;;基于多層面Rasch模型的TEM-4作文評分員效應(yīng)研究[J];中國外語教育;2015年03期

6 李航;;整體與分項(xiàng)量表的使用對EFL作文評分信度的影響[J];外語與外語教學(xué);2015年02期

7 黃志娥;謝佳莉;荀恩東;;HSK自動作文評分的特征選取研究[J];計(jì)算機(jī)工程與應(yīng)用;2014年06期

8 孫海洋;韓寶成;;英語寫作分項(xiàng)評分和整體評分比較研究[J];解放軍外國語學(xué)院學(xué)報(bào);2013年06期

9 劉力;麥陳淑賢;金檀;;寫作測試內(nèi)容質(zhì)量評分研究——分層決策樹法[J];現(xiàn)代外語;2013年04期

10 李銀玲;;關(guān)于提高作文評分信度的幾點(diǎn)啟示[J];英語教師;2013年08期

相關(guān)碩士學(xué)位論文 前4條

1 熊永燕;基于作文自動評分理論的小學(xué)寫作教學(xué)研究[D];華東師范大學(xué);2015年

2 陳東;基于文本特征提取的漢語L2作文電子評分系統(tǒng)初探[D];南京大學(xué);2013年

3 李亞男;漢語作為第二語言測試的作文自動評分研究[D];北京語言大學(xué);2006年

4 劉國偉;留學(xué)生漢語短文寫作中的客觀性成分及其對評分影響的分析[D];華東師范大學(xué);2005年

，

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