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Learner Corpus Research Group

Goals

The Learner Corpus Research Group VIP Team brings together undergraduate and graduate students who are interested in developing their knowledge of corpus linguistics, a computational research methodology widely used in linguistics. 

The project involves the collection and analysis of learner corpora in languages other than English. A learner ‘corpus’ is a large dataset of spoken and written texts by language learners stored and accessed in electronic format. The research activity of the VIP team will directly contribute to and expand the Multilingual Academic Corpus of Assignments - Writing and Speech (MACAWS).

 The types of research questions that the Learner Corpus Research Group will answer relate to language learners' use and development of language patterns (e.g., frequent words, phrases, grammatical structures, and other language features) in specific contexts. The research team will also work on the development and dissemination of corpus-informed language learning activities (see here for examples).

Issues Involved or Addressed

Our research areas include:

  • Language learning
  • Language teaching
  • Applied linguistics
  • Corpus linguistics

Methods and Tech

Our methods include:

  • Corpus linguistics (e.g., computational analysis, qualitative and quantitative coding of linguistic phenomena)
  • Classroom based research (e.g., survey, interview, observation) 

Academic Majors of Interest

Though open to all majors, we are most interested in students majoring in:

  • Spanish
  • East Asian Studies
  • English
  • Linguistics
  • Computer/Data Science

Preferred Interests and Preparation

  • Intermediate proficiency or higher in one of the languages covered in the VIP team (Spanish, Chinese)
  • Interest in language learning, language teaching, and/or corpus linguistics
  • Meets deadlines
  • Works well on a team
  • Attention to detail

Application Process

This team is currently full for the 2024-2025 school year. 

Team Advisors

Julieta Fernández, PhD

Shelley Staples, PhD

Yuwei Wang

Sara Matsumura