摘 要

本文以40篇中国大学生的英语作文中出现的写作错误为研究对象，经人工与自动评分系统分别进行检测与归类。这些英语作文是2013年“外研社杯”全国英语写作大赛复赛的作品，该比赛的参赛对象都是中国大学生。这次研究使用了iWrite这一智能写作评分系统来识别错误。本次研究采用了由外研社研发的新型智能写作系统iWrite来识别错误。本文将大学生写作错误分成了词法类、句法类、搭配类和技术规范四大类错误，而这四大类中又包含着34小类错误。通过对这些错误的识别与分类，本文探究了中国英语学习者写作中的错误频率以及自动评分系统对于各类错误的识别率。通过定量研究，本文在借助图表的基础上完成了对数据的分类，分析与解释。在经过统计分析后，研究结果表明：技术规范类是英语学习者在写作过程中最易犯的错误类型，其次是词法类错误与句法类错误。学生在搭配方面的错误相对较少。至于iWrite对于错误的识别率，本文发现iWrite对于技术规范类错误的识别率最高，对于搭配类错误的识别率则最低。

关键词： iWrite；错误分析；错误频率；错误识别率；中国英语学习者

Abstract

This paper investigated the errors recognized by human raters and Automated Essay Evaluation(AEE) system in 40 writings composed by Chinese English learners who study English as a second language(ESL), and provided an analysis on the frequencies of errors and the recognition rates of errors detected by AEE system-iWrite. The forty writings were written by Chinese university or college students who participated in the semi-final competition of the “FLTRP Cup” National English Writing Competition in 2013. The study employed iWrite system in the research, which was developed by Foreign Language Teaching and Research Press(FLTRP). The errors were divided into four categories, namely, morphology, syntax, collocation and mechanics, including overall 34 sub-types of errors. The data were classified, analyzed and interpreted through quantitative research, and presented in tables and charts. The findings of error frequencies suggested that mechanical errors were the errors most frequently made by ESL learners among the four categories, followed by morphological errors and syntactic errors. Students made relatively fewer errors in collocation. As for error recognition rates of iWrite, it was found that within the four categorizes, errors in mechanics had the highest recognition rate, while collocation errors owned the lowest recognition rate.

Key words: iWrite；error analysis；frequency of errors; recognition rate of errors；

ESL learners

Contents

1 Introduction 1

2 Literature Review 4

2.1 Theoretical framework 4

2.2 Review of related studies 5

3 Research Methodology 7

3.1 Research questions 7

3.2 Participants 7

3.3 Procedures 7

3.4 Data analysis 8

4 Results and Discussion 9

4.1 Frequency analysis of errors made by ESL learners 9

4.2 Recognition rates of errors recognized by iWrite 12

4.2.1 Overall recognition rates of iWrite 15

4.2.2 Detailed analysis of recognition rates of iwrite 15

5 Conclusion 19

5.1 Major findings 19

5.2 Implications 20

5.3 Limitations 20

5.4 Suggestion for further research 21

References 22

Appendix 25

Acknowledgements 27

Error Analysis of English Writings of Chinese ESL Learners Based on iWrite System

1 Introduction

English learners who study English as a second language (ESL) have the tendency to make errors in their English writing, which impairs their writing ability as well as bothers their teachers. In the late 1980s, researchers started to take an interest in ESL learners’ errors. According to Corder (1967) , the errors made by the ESL/EFL learners are significant because “they provide to the researcher evidence of how language is learned or acquired, what strategies or procedures the learner is employing in the discovery of the language” . James (1998) defined errors as “a register of their current perspective on the target language”. Many problems were discovered to be the causes for learners’ errors, including overgeneralization, ignorance of the rules of restriction, incomplete application of errors and false concepts hypothesized (Corder, 1971). James (1990) explored two potential of causes of errors: interlingual interference and intralingual interference. Interlingual errors are caused by the interference of the mother tongue. Intralingual errors are caused by the target language itself. Errors caused by learning strategies include analogy, grammatical errors, redundancy, over-correction and over-generalization (Alamin amp; Ahmed, 2012).

Automated Essay Evaluation (AEE) is a rather time consuming and expensive activity, the subjectivity of which can not be guaranteed during the grading process. Resorting to AEE systems, however, the students could get instant feedback and make revisions repeatedly, reducing the pressure as well as improving the effectiveness of teachers in essay evaluation (Grimes amp; Warschauer, 2010; Jiang, 2015). Grimes et al (2010) also found that conscious use of AEE could increase the motivation of students in writing and revision, allowing teachers to focus on higher level concerns instead of writing mechanics. AEE systems are applied not only in high-stakes commercial business, namely, testing companies, they are widely used to assist teachers in low-stakes classroom assessment, especially in universities as well. AEE systems abroad included Intelligent Essay Accessor (IEA), the Project Essay Grade (PEG), electronic essay rater (e-rater®), MY Access!®, Bayesian Essay Test Scoring System™ (BETSY) and so on ( Dikli, 2006). Those AEE systems mainly aim to assess essays written by native English students. As for ESL learners, the systems are limited in quantity as well as technology. In China, there are BingGuo English system, PiGai system and iWrite system for Chinese ESL learners to evaluate their English articles.