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Record W6941265358 · doi:10.11575/prism/35654

EAP Curriculum Alignment and Social Acculturation: Student Perceptions

2015· other· en· W6941265358 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2015
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAcculturationCurriculumMainstreamPerceptionEnglish for academic purposesQualitative researchSemi-structured interviewLanguage proficiency

Abstract

fetched live from OpenAlex

The role of English as a second language (ESL) teachers and instruction as fac- tors in student social and psychological acculturation is widely acknowledged. However, the function of English for Academic Purposes (EAP) is less well known in this regard, because research has focused largely on academic acculturation. This qualitative study investigated the perceptions of curriculum alignment with undergraduate study by post-EAP learners (students who had successfully completed EAP and were registered in mainstream university programs). Semistructured interviews were conducted with 7 former EAP students from a range of faculties at a large Canadian university. Analysis of interview data highlighted social acculturation as a perceived need in EAP curriculum, as participants remarked on linguistic and cultural barriers faced while participating in university life post-EAP. The researchers argue that social acculturation is typically underrepresented in EAP curriculum, and may be inadvertently overlooked by instructors, curriculum planners, and program providers.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2015
Admission routes1
Has abstractyes

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