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Record W4323530502 · doi:10.14288/bctj.v7i1.498

English for Academic Purposes in Canada: Results From an Exploratory National Survey

2022· article· en· W4323530502 on OpenAlexaffabout
James Corcoran, Julia Williams, Kris Pierre Johnston

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of WaterlooYork University
Fundersnot available
KeywordsSurvey researchExploratory researchPolitical sciencePsychologyMathematics educationMedical educationSociologyMedicineApplied psychologySocial science

Abstract

fetched live from OpenAlex

The growing trend of internationalization at Canadian institutions of higher education has led to increased need to support plurilingual students using English as an additional language (EAL). This support, often embedded in English for academic purposes (EAP) programs, is offered in a wide range of contexts across Canadian institutions of higher education. However, relatively little is known about this sector or those who work within it. In this article, we seek to delineate the Canadian EAP landscape by providing findings from the first phase of a mixed methods investigation into EAP programs and practitioners across Canada. We surveyed EAP programs and practitioners across three types of Canadian institutions involved in the provision of EAP support (n = 481). Findings point to a diversity of program models and practitioner profiles across Canadian regions and institutions, as well as significant differences in practitioners’ professional satisfaction based on role and institution type. Further findings point to substantial concern among EAP practitioners regarding job security, collaboration with other institutional stakeholders, and professional development opportunities. Adopting a critical pragmatic lens, we discuss findings, raising questions for consideration for EAP administrators, instructors, and post-secondary institutional policy makers, and conclude with a call for greater research into Canadian EAP programs and practitioners.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.000

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 head0.389
GPT teacher head0.504
Teacher spread0.115 · 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 designObservational
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

Citations5
Published2022
Admission routes2
Has abstractyes

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