A reassessment of frequency and vocabulary size in L2 vocabulary teaching1

By N. Schmitt, Diane Schmitt. Language Teaching, 2012

369 citations recorded by the source corpus.

The high-frequency vocabulary of English has traditionally been thought to consist of the 2,000 most frequent word families, and low-frequency vocabulary as that beyond the 10,000 frequency level. This paper argues that these boundaries should be reassessed on pedagogic grounds. Based on a number of perspectives (including frequency and acquisition studies, the amount of vocabulary necessary for English usage, the range of graded readers, and dictionary defining vocabulary), we argue that high-frequency English vocabulary should include the most frequent 3,000 word families. We also propose that the low-frequency vocabulary boundary should be lowered to the 9,000 level, on the basis that 8–9,000 word families are sufficient to provide the lexical resources necessary to be able to read a wide range of authentic texts (Nation 2006). We label the vocabulary between high-frequency (3,000) and low-frequency (9,000+) as mid-frequency vocabulary. We illustrate the necessity of mid-frequency vocabulary for proficient language use, and make some initial suggestions for research addressing the pedagogical challenge raised by mid-frequency vocabulary.

Subfields: Artificial Intelligence, Developmental and Educational Psychology, Language and Linguistics

View Paper: https://www.semanticscholar.org/paper/b032abfe15a34dbd444d3b8ae5cc478033c0958e

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In Artificial Intelligence

  1. N. Schmitt
  2. Paul Nation
  3. Diane Schmitt
  4. Marijana Macis
  5. T. Cobb
  6. Marlise Horst
  7. Stuart Webb
  8. E. Peters

In Developmental and Educational Psychology

  1. N. Schmitt
  2. Stuart Webb
  3. Paul Nation
  4. Diane Schmitt
  5. Marijana Macis
  6. T. Cobb
  7. Marlise Horst
  8. E. Peters

In Language and Linguistics

  1. N. Schmitt
  2. Paul Nation
  3. Marijana Macis
  4. Diane Schmitt
  5. T. Cobb
  6. Stuart Webb
  7. E. Peters
  8. F. Boers

Citations in the corpus