CLEC-based Study of Tense Errors in Chinese EFL Learners’ Writings

Abstract

In this dissertation, we conduct error analysis of the learner’s writing competence based on Chinese Learner English Corpus. According to the data from CLEC, the verb error heads the list among the tagged errors of different parts of speech. To address this issue, we set the following as research question of this study: 1. Which kind of error occurs most frequently among the tense errors in the sample writings in CLEC? 2. Are there any differences in the tense errors students committed within limited time and unlimited time? The writer has conducted an empirical Error Analysis by integrating error statistics and the corpus-based approach. Specific data for analysis have been obtained from CLEC and compositions written by the freshmen of non-English majors in Inner Mongolia Finance and Economics College. After a thorough analysis, we get the following major findings:

1. On the whole, most of the sixteen categories of misuse of tenses are widespread among the five corpora. Although the students of each corpus have different language proficiencies, present tense and past tense are the two most frequently misused tenses in every corpus, while all kinds of future tenses except future tense itself and all kinds of past future tenses except past future tense itself are the least frequently misused tenses in each corpus.

2. Generally speaking, the sixteen categories of tense errors distribute more evenly in free writings and the error rates of the same tense are different in CLEC and in free writings, which shows that the time limit can indeed affect the students’ performance on tense errors.

3. The causes leading to verb errors are mother tongue influence, target language influence and cognitive factors.