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Record W1909802662 · doi:10.24908/pceea.v0i0.4819

A SUCCESSFUL APPROACH TO EDUCATING ENGINEERING LEADERS AT THE GRADUATE LEVEL

2013· article· en· W1909802662 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2013
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsEngineering managementEngineeringLeadership developmentValue (mathematics)Engineering educationEngineering ethicsComputer sciencePolitical sciencePublic relations

Abstract

fetched live from OpenAlex

We need to develop future engineering leaders who have the capability to lead teams in efficiently and effectively delivering projects and products for their stakeholders.This paper describes the methodology used by the Gordon Engineering Leadership Program at Northeastern University to teach Engineering Leadership at the graduate level to achieve this goal.The approach utilized in the Gordon Engineering Leadership Program (GEL) involves an integrated course which has a close alignment with industry and leverages five primary elements: Leadership Capabilities, Leadership Laboratories, Product Development, Scientific Foundations and a Challenge Project. This paper outlines two critical areas, the use of a leadership capability framework linked to interactive leadership laboratories and the use of mentoring to maximize the educational value of the “Challenge project”.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.228
Teacher spread0.198 · 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