Pedagogical rationale for «Raising the Bar 5»: using research and best practice methods to inform textbook features
Bibliographic record
Abstract
The Enriched English as a Second Language (EESL) program is relatively new in the province of Quebec. The Ministry has provided guidelines and set outcomes that must be reached by the end of secondary 5 yet there are very few resources for teachers at this level. This thesis explores the research on best practices in teaching advanced English to Second Language students and blends practices used in English as a Second Language and English Language Arts classes. It examines this research in relation to the EESL textbook I co-authored entitled Raising The Bar 5. The literature review encompasses research on grammar, vocabulary, literary analysis, listening exercises, multimedia technology as used for group work, and the peer response process, as they relate specifically to teaching of advanced and enriched English as a Second Language. The research explores each of the specific aspects of the textbook and offers insight into the EESL pedagogies and the textbook's approach, in addition to pointing out areas for improvements for subsequent editions and textbooks in the same series.
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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 | 0.128 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.009 | 0.056 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".