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Record W2604983992 · doi:10.24908/pceea.v0i0.6467

HIGH SCHOOL STUDENTS’ VIEWS ON ENGINEERS CANADA’S DEFINITION OF PROFESSIONAL ENGINEERING WORK

2017· article· en· W2604983992 on OpenAlexafffundvenueabout
Scott Compeau, David Strong

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2017
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAccreditationScope (computer science)Work (physics)Engineering educationCareer pathEngineering ethicsPerceptionHealth systems engineeringEngineeringMedical educationEngineering managementPsychologyComputer scienceMedicineMechanical engineering

Abstract

fetched live from OpenAlex

The breadth of the engineering profession is illustrated by Engineers Canada’s (EC) recognition of over 120 accredited engineering programs across the country. Arguably, the work of a professional engineer spans over an even larger scope. However, synthesizing a description of engineering work that encompasses all aspects of the profession is extremely difficult. Applicants to engineering programs in Canadian universities require high standing in specific course pre-requisites. In order to make an informed decision with regard to engineering as a possible career path, it is critical that students clearly understand the engineering profession. The purpose of this paper is to describe how Grade 9/10 students’ perceptions of engineering work compares to EC’s description, based on the outcomes of a research study involving a questionnaire and interviews. The findings show that the emerging categories from these students’ descriptions of engineering work that aligns with EC’s description, involves design (42.3%) and helping people or the environment (16.5%).

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)0.007
metaresearch head score (Gemma)0.011
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 score0.096
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0140.006
Scholarly communication0.0090.001
Open science0.0010.004
Research integrity0.0010.003
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 head0.009
GPT teacher head0.212
Teacher spread0.204 · 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
Published2017
Admission routes4
Has abstractyes

Explore more

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