MétaCan
Menu
Back to cohort
Record W1880771316 · doi:10.24908/pceea.v0i0.4832

DEVELOPING AN ENTREPRENEURIAL MINDSET IN ENGINEERING STUDENTS

2013· article· en· W1880771316 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2013
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMindsetEntrepreneurshipEngineering educationCurriculumEngineering managementEngineering ethicsEngineeringManagementPedagogyPsychologyBusinessComputer science

Abstract

fetched live from OpenAlex

Developing engineers with entrepreneurial skills is becoming a valued objective for engineering faculties across the country. Entrepreneurship courses are being added to engineering curriculum, course options are being created to allow students to pursue an entrepreneurship or management track in their undergraduate engineering studies, and graduate programs are being developed in Engineering Management, as a more specific and alternative route to the Master of Business Administration (MBA). This paper presents the results of a six-year survey of engineering students who have elected to enroll in an upperclassmen Entrepreneurship course. It presents the approach that has been taken in an Engineering elective at Memorial University to develop entrepreneurially minded engineering students, and the students’ perspectives on why engineers become entrepreneurs, what entrepreneurial qualities they believe they possess, and how they have learned to evaluate entrepreneurial ideas not only on its technical merit, but organizationally and strategically.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.008
GPT teacher head0.228
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