Implementation of the CEFR in the rubrics of two main English Certificates: Cambridge FCE and Trinity ISE-II.
Bibliographic record
Abstract
The Common European Framework of Reference (CEFR) was developed by the European Council with the intention of providing a comprehensive basis for the creation language syllabi and curriculum guidelines, together with the design of teaching materials, language certificates and instruments of assessment. The CEFR has been implemented in Spain through different education laws and has prompted the introduction of the communicative approach and the use of new instruments of assessment such as rubrics. Nonetheless, almost twenty years after the CEFR was passed, not many researches have been conducted on how the Framework has been implemented. It is from this line where the current research stems as it intends to check how the CEFR has been adapted in the rubrics used for the assessment of the writing skill in two main English Certificates: the Cambridge Assessment English FCE and the Trinity College ISE-II. El Marco Común Europeo de Referencia (MCER) se desarrolló con el objetivo de promover una base común para la creación de currículos educativos y servir como guía en la elaboración de materiales didácticos, exámenes de certificación e instrumentos de evaluación. El MCER se ha implantado en España a través de diferentes leyes educativas y ha propiciado la introducción del enfoque comunicativo o nuevos instrumentos de evaluación como rúbricas. Sin embargo, casi veinte años después de la aprobación del marco, pocos son los estudios que han revisado de qué manera se ha adaptado el marco. Es aquí donde la presente investigación se sitúa, con el objetivo de comprobar cómo se ha implementado el MCER en las rúbricas para examinar la destreza escrita de dos de los principales certificados de inglés: el Cambridge Assessment English FCE y el Trinity College ISE-II.
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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 | 0.030 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".