Using Google as a super corpus to drive written language learning: a comparison with the British National Corpus

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Second Language Acquisition and Learning Lexicography and Language Studies English Language Learning and Teaching

Abstract

Data-driven learning (DDL), or corpus-based language learning, involves the learner in an exploratory task to discover appropriate expressions or collocates regarding his writing. However, the problematic units of meaning in each learner's writing are so diverse that conventional corpora often prove futile. The search engine Google with the characteristics of dynamic corpora can provide quantitative parameters for evaluating a chunk of language. This article describes an experiment in which DDL was accomplished with the aid of Google and presents the evaluation of the outcome based on a comparison of Google and the British National Corpus (BNC) and eventually reaches the conclusion that the dynamic corpus or search-engine-based corpus is superior in usability, search speed, the number of solutions and above all, preference investigations.

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1991Teaching English as a second or foreign language 2002Corpora in Applied Linguistics 2022Corpora in Applied Linguistics 2000Formulaic sequences in second language teaching: principle and practice 1998The BNC Handbook: Exploring the British National Corpus with SARA 2014Teaching and Language Corpora 2003Probabilistic Linguistics 2006A Glossary of Corpus Linguistics

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2015Applying data-driven learning to the web 2016Cultivating effective corpus use by language learners 2023Data-driven learning (DDL) activities: do they truly promote EFL students’ writing skills development?2011Phraseology and frequency of occurrence on the web: native speakers’ perceptions of Google-informed second language writing

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