Evaluating lists of high-frequency words: Teachers’ and learners’ perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.000 |
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 it