A Computer Corpus-Based Study of Chinese EFL Learners’ Use of Adverbial Connectors and Its Implications for Building a Language-Based Learning Environment

Abstract

This research adopts the methodology of corpus-based analysis and contrastive interlanguage analysis (CIA), using three corpora as the data source to analyze the adverbial connectors used by Chinese EFL (English as a foreign language) learners (i.e., university students in Guangzhou, China) in their written English. Major findings show that Chinese EFL learners have displayed a general tendency to overuse English adverbial connectors in terms of total tokens when compared with native speakers of English, and Chinese EFL learners deviate notably from the native speakers of English in the use of some individual English adverbial connectors. The research explores that Chinese EFL learners’ use of English adverbial connectors might be influenced by L1 transfer, writing handbooks’ and teachers’ instruction, learners’ lack of audience awareness, and lack of stylistic awareness. The research has some implications for language learning: a large collection of learner corpora, a target language's native speakers corpus, a learner's mother language corpus, and corpus software AntConc can complement textbooks in language learners’ deep learning process, constituting a language-based learning environment for human languages with reduced perplexity and increased accuracy.