Application Of Corpus-based Data-Driven Learning Model In College English Vocabulary Teaching And Learning

It is well known that vocabulary plays a very important role in language learning because it is the core of a language and vocabulary learning is central to language acquisition. With the guidance of the new teaching notion advocated by College English Curriculum Requirements, English teaching should be based on modern information technology, particular network technology. Therefore,corpus-based Data-Driven Learning (DDL) model has become the tendency for college English learners'efficient and autonomous learning.Corpus linguistics is the backbone theory of this research. As an assistant tool in language education,corpus is a new study field in applied linguistics.Based on a large collection of authentic materials and advanced software,corpus facilitates learning by making linguistic patterns more easily detectable for learners to work out solutions to real language problems. Corpus can be applied in various aspects of lexical learning, which provides a good platform for teaching and learning vocabulary, especially in collocation, word-meaning in different contexts and lexical grammar structure.The nature of learning through concordancing is well summed up in the term―Data-Driven Learning‖(DDL) proposed by Tim Johns (1991). DDL is defined by Johns as―the use in the classroom of computer-generated concordances to get students to explore regularities of patterning in the target language and the development of activities and exercises based on concordance output‖. What's more, this model, which makes use of the abundant authentic language inputs provided by the corpora, gathers the features of―authentic‖contexts,―multiple-occurring‖input, and―self-detecting & self-discovery‖. The DDL provides multitudes of organized language data on demand, and learners analyze the data to generalize rules for the language.Tim John also describes DDL'procedures of Identify-Classify-Generalize. (1) Identifying: learners or teacher identify the questions under examination.(2) Classifying: students take on the active roles of researchers, sorting through massive language data to discover rules and patterns embedded in the data. (3) Generalizing is interpreting language data and generalizing from them to solve problems. This procedure represents an important part of the learning process because learners analyze the data to figure out patterns of language use.In the past two decades, DDL has thrown new light on the basic assumptions on English vocabulary. This paper applies DDL to vocabulary teaching. Generally, researchers view vocabulary knowledge from two dimensions: the breadth of vocabulary knowledge and the depth of vocabulary knowledge. These two dimensions offer a rich framework for describing different aspects of vocabulary knowledge. When we teach vocabulary, we should not only pursue the increase in the quantity, that is the breadth of vocabulary, but also help learners to improve the quality of word knowledge, the depth of vocabulary.The thesis centers on the application of corpus-based DDL model in college English vocabulary teaching and learning, especially in depth of vocabulary knowledge: collocation, word-meaning in different contexts and lexical grammar structures. The subjects of this study were two classes of 86 non-English-major second-year undergraduate students from Northwest Normal University. Class one was randomly selected as the control group and Class two the experimental group. The traditional method was used for the control group while the experimental group received corpus-based DDL model. Two tests on vocabulary were administered as the pre-test and post-test to check the effects of the treatments. The obtained data were then submitted to different statistical analyses such as Paired-samples T-test and one-way ANOVA test in SPSS 17.0.The results of this analysis showed that there was a significant difference between the pretest and posttest of experimental group. (P=0.000<0.05) What's more, in the posttests, the participants who took DDL showed to be surely superior to those who received instruction in the conventional approach. ( t=-3.640, P=0.001<0.05. ) Therefore, DDL model as a supplementary means of teaching vocabulary has played a significant role in enhancing students learning collocation, word-meaning in different contexts and lexical grammar structure. Compared with the traditional learning method,the DDL model has some superiority and it is effective in college vocabulary teaching and learning. Applying the DDL model will,undoubtedly, contribute a lot to vocabulary teaching and learning.It should be pointed out that no matter how valuable a corpus may be,it is still a tool,and it cannot replace the textbooks and classroom instructions.Using DDL is only one of supplements to the many traditional methods of learning the vocabulary. And the thesis shows some insight into a lexical learning model by a tentative application of the corpus,while there are still some limitations.Finally, this thesis is only a preliminary study about application DDL in college English vocabulary teaching and learning, and more further research should be conducted on the function of corpus-based DDL in the future.