Abstract
As data-driven learning has been advancing across new frontiers in recent years, there is still a paucity of studies on data-driven vocabulary learning model that brings about effectiveness in teaching and learning practices. Idiomaticity, which serves as an important indicator for language proficiency, needs abundant contextualized language input for the acquisition of target words. In this regard, the present study explores whether computer-assisted language learning is effective in vocabulary acquisition, and in the differentiation of synonymous words on the part of learners. Pre-/posttests and questionnaires were administered among an experimental group (N=26) and a control group (N=26). Results showed that the experimental group, who was instructed under the data-driven learning model, got a higher mean score than the control group, who received traditional dictionary-consulting instruction. The former also finished the posttest within a much shorter period of time. A significant relationship was found between the pretest scores and posttest scores among the experimental group whereas the scores in the control group did not reach statistical significance. Therefore, there was a significant improvement in learners’ performance on collocation production under the data-driven learning model, whilst dictionaries did not prove to have such a contributing effect. This study provides some suggestions for how to enhance learners’ idiomaticity by improving collocation performance under the data-driven model.
Highlights
Vocabulary is the building block of a language
The present study set out to design a data-driven vocabulary learning model based on COCA, and to investigate whether the model boosts effectiveness compared with traditional vocabulary learning
As the building block of a language, vocabulary acquisition has long been on the center stage of second language learning
Summary
Vocabulary is the building block of a language. As a celebrated quotation goes, without grammar very little can be conveyed; without vocabulary nothing can be conveyed [1]. Vocabulary teaching in an English as a second or foreign language setting has long been occupying a central position in second language classrooms. With the development of computer technologies and educational sciences, vocabulary pedagogical approach has undergone major shifts in recent years. The last few years have seen a rapid development in computerized linguistic resources for the acquisition of L2 vocabulary. Computer-based language learning, or data-driven learning (DDL), has revolutionized traditional ways of learning. Traditional instruction has gradually iJET ‒ Vol 15, No 23, 2020
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