A Corpus-based Study Of College English Vocabulary Teaching

The writing of this paper is based on practical concern and theoretical inspiration. With the development of education reform, College English Curriculum Requirements put forward a higher standard of vocabulary knowledge for college students, apart from learning enough vocabulary, students have to learn to use vocabulary appropriately. College English Curriculum Requirements reflect the notion of enlarging the depth of vocabulary knowledge.However, being affected by traditional vocabulary teaching and learning method and vocabulary acquisition theory, which emphasized too much on the breadth of vocabulary and ignored the depth of vocabulary, students’ ability to use vocabulary is far more than being satisfied. Their motivations and abilities of autonomous learning are low. How to improve the quality of vocabulary teaching and learning, as well as enhancing their motivation and learning autonomy become a heated topic. The theoretical inspiration comes from the application of corpus concordance and Data-Driven Learning.With the progress of modern information technology, corpus has been widely used in vocabulary teaching and learning, however, only some of them concerned about putting it into specific aspects of the depth of vocabulary teaching and learning. Therefore, this paper focuses on the application of corpus-based DDL model in college English vocabulary teaching and learning, and tries to find a method to apply it to private college English class.The subjects were 83 non-English-major freshmen chosen from Minnan University of Science and Technology, they are majoring in financial management. Class 5 was randomly selected as the control group and class 7 the experimental group. The former used the traditional methods while the latter received corpus-based DDL model. Both pretest and posttest of vocabulary were carried out in each group, and class 7 also filled out a questionnaire. All the data collected were submitted to statistical analysis such as Independent-samples T-test and Paired-samples T-test in SPSS17.0. The results showed that there was a significant difference between the experimental class and the control group in the post test(P=0.016<0.05), and there was a significant difference between the pretest and posttest of experimental group(P=0.000<0.05). In other words, compared with traditional method, corpus-based DDL model did help students learn better in the aspects of collocation, colligation and context meaning of vocabulary while developed their ability of autonomous learning. However, the author also noticed that corpus-based DDL model was not suitable for some students; we can integrate the corpus-based DDL model with traditional teaching method.