Contextualising the CEFR: the Universiti Malaysia Pahang english language proficiency writing test
Bibliographic record
Abstract
The Common European Framework of Reference for Languages (CEFR) has made a significant impact on language testing worldwide, particularly on the English language proficiency test (EPT). Many countries including the United States, Canada and Australia have begun aligning their language assessments with CEFR. Although it has been applied worldwide, CEFR arguably lacks connection with stakeholders, socioeducational contexts as well as empirical validation. Much of the criticism revolves around a neglect of non-European contexts. Studies which concentrated on both directly and indirectly CEFR-aligned English language tests within the contexts of Asian countries such as Japan and Taiwan have been published. In Malaysia, its English Language Roadmap 2015-2025 takes into consideration aspects of teaching, learning and assessment of the English language based on the six CEFR levels. Therefore, higher education institutions will need to respond to this roadmap by aligning their English language tests to these standards. Nevertheless, to date, no similar studies have been documented within the context of Malaysia. Hence, this paper seeks to fill the gap in the literature by presenting the early stage works on the contextualisation of the comprehensive yet non-exhaustive CEFR to suit the needs and demands of Universiti Malaysia Pahang English Language Proficiency Test stakeholders. The present study has given emphasis on writing because it is usually considered the most important at tertiary level education. Through writing, language functions not only as the transmitter of knowledge or enabler for communication but also as a mediating tool for the thinking process that is manifested in written form. Aligning locally-developed EPT to the CEFR standards will not only provide evidence of test takers’ level of proficiency but the alignment will also give the local EPT a value-added advantage in terms of the marketability of the CEFR-aligned EPT.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".