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Record W3097451207 · doi:10.5539/ijel.v11n1p1

Going Global: The Successful Link of IELTS and Aptis to China’s Standards of English Language Ability (CSE)

2020· article· en· W3097451207 on OpenAlexvenueno aff
Xueliang Chen, Jie Hu

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesZhejiang University
KeywordsCurriculumInternationalizationChinaContext (archaeology)Test of English as a Foreign LanguageScale (ratio)Language proficiencyLanguage assessmentMathematics educationPsychologyPedagogyPolitical scienceGeographyBusiness

Abstract

fetched live from OpenAlex

The development of a common language proficiency scale is essential to language teaching, learning, and assessment. While some general English proficiency scales already exist, no such scale is available in an Asian context. China’s Standards of English Language Ability (CSE), as the first scale of its kind, promises to address this deficiency with a clear focus on the student population, grounded in the well-established framework of communicative language ability. As such, it not only illuminates the learning patterns of English language learners at different stages, but also provides a benchmark for curriculum design, student evaluation, and the improvement of educational programs. More importantly, its recent link with such international tests as Aptis and IELTS marks a significant step towards the internationalization of this scale, making student grades on different tests more comparable. The official mapping of CSE to the international examination system opens China’s education further to the rest of the world, and would facilitate student exchanges and deepen educational ties between countries in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.101
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.101
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.275
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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