Article published in:
Spanish Learner Corpus Research: Current trends and future perspectives
Edited by Margarita Alonso-Ramos
[Studies in Corpus Linguistics 78] 2016
► pp. 33–52

Chapter 2
What is missing in learner corpus design?

| Tokyo University of Foreign Studies

This chapter discusses what is missing in learner corpus design. Learner corpus researchers are sometimes not fully aware of the basic principles of corpus design and collection that most corpus linguists should know. I will first discuss theoretical and methodological issues related to learner corpus design and collection, focusing on sampling, representativeness, and corpus size. Then, I will review three relevant studies (Biber 1993; Tomasello & Stahl 2004; Mukherjee & Rohrbach 2006) in order to better understand corpus design issues such as parameters of corpus sampling, effects of sample size, and variations in learner corpus design. Finally, the chapter concludes by discussing critical assessment and future directions in terms of issues of design as well as data collection in learner corpus research.

Keywords: corpus design criteria, sample size, representativeness, data collection
Article outline
  • 1.Introduction
  • 2.What learner corpus researchers should know before using or creating corpora
    • 2.1Basic concepts of corpus design and collection
      • 2.1.1Machine-readability
      • 2.1.2Authenticity
      • 2.1.3Sampling
      • 2.1.4Representativeness
    • 2.2Pitfalls in designing learner corpora
      • 2.2.1Target population
      • 2.2.2Data collection methods
      • 2.2.3Subcorpus design
  • 3.Meeting criteria in learner corpus design
    • 3.1Sampling which reflects a full range of variability
    • 3.2Effects of sample size
    • 3.3Possible variations in learner corpus design
  • 4.Critical assessment and future directions
    • 4.1Issues of balance and representativeness
    • 4.2Data collection issues
  • References
Published online: 16 December 2016
https://doi.org/10.1075/scl.78.02ton
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