High Frequency Vocabulary in a Secondary Quebec ESL Textbook Corpus
Bibliographic record
Abstract
It is widely accepted that high-frequency vocabulary must be taught in ESL/EFL classrooms, and that learners benefit from learning it (Schmitt, 2011; Nation, 2001). Research also confirms that recycling vocabulary is beneficial in facilitating the acquisition of vocabulary knowledge Milton (2009). In order to understand the lexical characteristics of classroom input secondary ESL learners in Québec are exposed to, I gathered and analyzed a corpus of Ministry-approved textbooks (Collection Quest for cycle 2 published by Chenelière Éducation). Subsequently, I used the corpus findings to develop a pedagogical word list that targets high frequency words that may need more emphasis or be missing entirely. Results showed that there are considerable deficits in the vocabulary presented in the three books. The 1k level was considered well represented because most words at this level occur in the books frequently and are widely recycled across the volumes. At the 2k and 3k levels, most words also occur in the books; however their frequency and range of occurrence are not satisfactory in terms of promoting successful acquisition. As for the mid-frequency vocabulary, results show that students have very few opportunities to encounter these words in their books. Most of the words between the 3k and the 9k levels are not recycled frequently in the corpus.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".