The purpose of this master's project was to write a resource book that demonstrates how teachers can use data-driven learning methods to teach vocabulary. First, a brief overview of corpus linguistics, data-driven learning, and the corpus used in this book (COCA) is given. Then, the book presents different aspects of vocabulary learning in the context of a corpus. Topics included are frequency knowledge, part of speech knowledge, morphological knowledge, synonym knowledge, collocational knowledge, and register knowledge with a chapter on each topic. For each aspect of vocabulary learning there is a section that introduces the topic to the teacher, followed by instructions on performing topic related searches in the corpus. Each chapter also includes examples and ideas for application to the vocabulary classroom. Additional chapters provide information on individual language learning, and an evaluation of the project. The goal of this project was to provide teachers with specific knowledge of vocabulary and corpus-linguistics to be able to teach less-frequently addressed aspects of vocabulary instruction and to encourage more use of corpora in the language classroom. It is hoped that after reading this book, teachers will be able to improve their vocabulary teaching and ability to use the Corpus of Contemporary American English and DDL methods in the ESL/EFL classroom. The evaluation of this project will consist of teacher reviews of the book after reading. Specifically, the questionnaire addresses readers' feelings of increased knowledge and understanding of these areas and desire to use them in the classroom.
College and Department
Humanities; Linguistics and English Language
BYU ScholarsArchive Citation
Shaw, Erin Margaret, "Teaching Vocabulary Through Data-Driven Learning" (2011). Theses and Dissertations. 3024.
COCA, data-driven learning, vocabulary teaching, metalinguistic awareness, DDL