Young Learners and Lexical Awareness: Children's Engagement With Wordlists and Concordances
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
Sinclair (1991) found that lexical analysis can be overcomplicated, yet Johns (1994) called for investigation into whether corpus analysis can motivate beginners and near‐beginners. The findings of this research suggest that young EFL learners can enjoy using corpus analysis tools (wordlists and concordances) to identify, classify, and generalize about English. The teacher‐researcher developed a series of classroom activities in which students created wordlists and discovered and recorded collocations. Quantitative data gathered over 1 year from yes/no and ranking questions indicate that students found the activities enjoyable, and 230 write‐in comment sheets provided qualitative data that support the motivational impact of the activities. Findings suggest that as corpora, particularly of children's language, are created and expanded upon, it is vital that classroom activities developed to target meaningful young learner language present this relevant language in an enjoyable, engaging manner.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.030 | 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