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Record W4400391707 · doi:10.37213/cjal.2024.33259

Developing and validating a post-admission screening-diagnostic assessment procedure to offer language support in diploma programs

2024· article· en· W4400391707 on OpenAlexaffvenue
Nathan J. Devos, Deo Nizonkiza, Sarah Lynch

Bibliographic record

VenueCanadian Journal of Applied Linguistics · 2024
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsUniversity of British ColumbiaBritish Columbia Institute of Technology
Fundersnot available
KeywordsVocabularyLanguage assessmentMedical educationComputer sciencePsychologyMedicinePedagogyLinguistics

Abstract

fetched live from OpenAlex

As post-secondary institutions assume more responsibility for the language abilities of their graduates, more attention is being paid to post-admission language support to enhance student success. Previous research has indicated that a post-admission language diagnostic assessment procedure, when coupled with language support services, can be an effective model in helping students meet language expectations in post-secondary settings. This paper outlines the development and validation of a screening-diagnostic assessment procedure to recommend students to language support services in diploma programs. Our key findings suggest that testing vocabulary can be an effective measure for screening language abilities and that students who receive a recommendation through the procedure and subsequently attend language support classes have higher communication grades than those who do not attend. These results offer validity evidence for the use of this procedure while ongoing research is being conducted to continue to validate its testing measures.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.339
Teacher spread0.317 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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