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Record W1878999124 · doi:10.24908/pceea.v0i0.4783

EFFECTS OF FIRST-YEAR INTEGRATED WRITING AND DESIGN

2013· article· en· W1878999124 on OpenAlexafffundvenue
Suzan Last, Peter Wild, Geri Van Gyn

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2013
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsReading (process)Mathematics educationEmphasis (telecommunications)Course (navigation)PsychologyComputer scienceMedical educationEngineeringMultimediaMedicineLinguisticsTelecommunications

Abstract

fetched live from OpenAlex

This paper presents the results of a two yearassessment study (2010-2012) that compares the writingoutcomes of engineering students who completed a newlydesigned integrated first year Communications andDesign course (ENGR 110) to the achievements ofEngineering students who had taken the traditional firstyear composition course previously offered toengineering students. The purpose of the study was todetermine if the new course design, with its emphasis onengineering-specific reading and writing content, as wellas written assignments based on students’ design labactivities, enhanced students’ achievement of writingskills. The results show moderate to significantimprovement in all but one of the assessed skills,indicating that the new integrated course design has beensuccessful in achieving its goals.

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)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.003
GPT teacher head0.156
Teacher spread0.154 · 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

Citations0
Published2013
Admission routes3
Has abstractyes

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