An inquiry into concept mapping as a form of pre-task planning in adult Japanese ESL learners' essay writing
Bibliographic record
Abstract
This study investigated concept mapping as a form of pre-task planning in ESL (English as a Second Language) learners' writing performance. I observed during regular class periods the writing practices of 3 adult Japanese learners enrolled in a writing program at a private ESL school in Toronto. I then analyzed 4 of the learners' compositions written with and without concept mapping, using measures of accuracy, complexity, fluency and following Hamp-Lyons' (1991) holistic measures. I examined through a questionnaire, retrospective interview and logs the students' applications of the strategy in their writing processes. Pre-task planning was associated positively with the overall measures of the learners' written production during in-class compositions, except for accuracy. However, each learner made unique applications of the concept mapping strategy in their writing processes, suggesting that concept mapping may help ESL learners improve their composing but in unique ways according to individual experience, motivation, and task conditions.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".