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Record W2105740573 · doi:10.47678/cjhe.v42i1.182449

Educational Outcomes of English Language Learners at University

2012· article· en· W2105740573 on OpenAlexaffvenueabout
Hetty Roessingh, Scott Roy Douglas

Bibliographic record

VenueCanadian Journal of Higher Education · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsEllEnglish languageAcademic achievementLiteracyMathematics educationPsychologyPoint (geometry)PedagogySociologyTeaching method

Abstract

fetched live from OpenAlex

This study compares the undergraduate academic achievement of domestic English language learners (ELLs) of different age on arrival (AOA) cohorts to native English speakers (NS), all of whom graduated from local high schools. The broad research question that frames the study is how the literacy levels of ELLs of different AOA cohorts influence retention, progress, and grade point average (GPA) as indicators of academic success. Findings suggest that ELLs are resilient and determined as they make progress toward degree status. However, their progress and achievement, regardless of AOA, is fraught with challenges. This outcome represents a loss of educational capital for Canada in an economy that needs the participation of these students, who are among our brightest and best. Suggestions are made for policy reform, pedagogy, and service provision for ELLs at university.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.015
GPT teacher head0.235
Teacher spread0.220 · 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 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

Citations29
Published2012
Admission routes3
Has abstractyes

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