Evaluating lists of high-frequency words: Teachers’ and learners’ perspectives
Bibliographic record
Abstract
With a number of word lists available for teachers to choose from, teachers and students need to know which list provides the best return for learning? Four well-established lists were compared and it was found that BNC/COCA2000 (British National Corpus / Corpus of Contemporary American English 2000) and the New General Service List (New-GSL) provided the greatest lexical coverage in spoken and written corpora. The present study further compared these two lists using teacher perceptions of word usefulness and learner vocabulary knowledge as the criteria. First, 78 experienced teachers of English as a second language / English as a foreign language (ESL/EFL) rated the usefulness of 973 non-overlapping items between the two lists for their learners. Second, 135 Vietnamese EFL learners completed 15 yes/no tests which measured their knowledge of the same 973 words. Teachers perceived that the BNC/COCA2000 had more useful words. Items in this list were also better known by the learners. This suggests that the BNC/COCA2000 is the more useful high-frequency wordlist for second language (L2) learners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".