Raising awareness about the diversity of anglophone territories and cultures in the efl classroom
Bibliographic record
Abstract
ABSTRACT: This dissertation is an innovative educational proposal designed to solve a specific weakness detected during my experience in the Practicum period of the Master’s course in the charter school Escuelas Pías Pompiliano, located in Zaragoza. After examining the coursebook used in the classroom, I could observe that there was a dominant presence of the United Kingdom and the United States of America in the activities it proposed, which concluded in the lack of representation of other English-speaking communities. Thus, territories belonging to the “Inner Circle” of English like Canada, Australia, New Zealand, South Africa and the Republic of Ireland were given a limited or inexistent representation in the EFL classroom, which didn’t provide a complete consciousness and understanding of the wide diversity of English-speaking communities. The Unit Plan will therefore propose a solution to this detected gap, incorporating cultural, historical and geographical aspects from those countries throughout the activities of the lessons in order to normalise their presence in the EFL classroom. This dissertation will consider academic works and studies regarding the importance of providing cultural diversity in the EFL classroom, as well as the legal provisions specified in the LOMCE and the Aragonese Curriculum, following their indications regarding the importance for students to value their own and others’ culture and history, as well as the necessity to educate them in terms of diversity and respect to other languages and cultures.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".