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Challenges in Corpus Linguistics: Rethinking corpus compilation and analysis
Edited by Mark Kaunisto and Marco Schilk
[Studies in Corpus Linguistics 118] 2024
► pp. 55–67

Challenges in the compilation, annotation, and analysis of learner corpus data

| University of Bremen

This chapter highlights and discusses the special characteristics of learner corpus data and the challenges they may present for corpus compilation, annotation, and analysis. Because learner corpus and SLA researchers use their data to study L2 production and development, it is of utmost importance that the data are valid, that is, they represent “authentic” L2 production, which means that the data must stem from the studied learners’ own language production. This chapter discusses challenges in three areas: (1) multilingual practices and metalinguistic language use, (2) lexical and constructional bias, often brought about by the wording of task instructions or writing prompts that learners are asked to respond to, and (3) learner corpus annotation in view of the “discourse of deficit” in SLA. For each of these challenges solutions as to how they can be met are offered.

Keywords: learner corpus, compilation, analysis, annotation, multilingualism, lexical bias, task instruction, writing prompt, discourse of deficit, lexical innovation
Article outline
  • 1.Introduction and general remarks
  • 2.Challenges and how to respond to them
    • 2.1Multilingual practices and metalinguistic language use
      • Response
    • 2.2Task effects
      • Response
    • 2.3“Discourse of deficit” and learner corpus annotation
      • Response
  • 3.Summary and conclusion
  • Notes
  • References
This content is being prepared for publication; it may be subject to changes.
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