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Record W2910347971 · doi:10.24908/pceea.v0i0.12960

The Right Tools for the Job: Discipline-Specific Language-Learning for First-Year International Engineering Students

2018· article· en· W2910347971 on OpenAlexaffvenue
John Pringle, Gabriel Potvin

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDisciplineComputer sciencePerceptionMathematics educationGeneral partnershipCommunication skillsPsychologyMedical educationPedagogySociology

Abstract

fetched live from OpenAlex

Vantage College at UBC offers specialized first-year programs for international students that integrate core disciplinary courses with complementary language education to allow students to develop their communication skills before joining their direct-entry counterparts for the remainder of their studies. This paper builds on the partnership between two first year engineering chemistry courses and their adjunct language courses, in which the instructors work closely together to accomplish mutual learning objectives. As a measure of the effectiveness of this integrated approach on the development of discipline-specific communication skills, the frequency of specific language error types are tracked in student’s lab reports, across two terms, and students report through a survey their perception of how this integrated approach helped them develop their technical communication skills. Overall, as indicated by both significant reductions in the frequency of several error types, as well as the responses provided by students, this integrated approach is effective, and the data suggests key areas of focus for further improvement.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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.

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

Citations2
Published2018
Admission routes2
Has abstractyes

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