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Record W3036180169 · doi:10.24908/pceea.vi0.14129

BUILDING THE ENGINEERING MINDSET: DEVELOPING LEADERSHIP AND MANAGEMENT COMPETENCIES IN THE ENGINEERING CURRICULUM

2020· article· en· W3036180169 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) · 2020
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of GuelphUniversity of Alberta
Fundersnot available
KeywordsMindsetHealth systems engineeringCompetence (human resources)CurriculumEngineeringEngineering ethicsEngineering managementEngineering educationManagementComputer sciencePedagogySociology

Abstract

fetched live from OpenAlex

In this paper we explore building the engineering mindset from the perspective of developing exceptional leadership and management competencies to guide and support the traditional technical competencies that are the primary focus of undergraduate engineering programs. A knowledge base for engineering, science, and design is developed throughout most engineering programs. Math and science are carefully scaffolded from first year engineering to ensure technical competence by graduation. We ask the questions: “How are leadership and management related to engineering work and design?” and “Can we develop a framework to guide the development of leadership and management skills in the engineering curriculum?” We argue leadership and management are integral to the engineering mindset and necessary to address the complex engineering problems society faces. There is discord between the responsibility of the engineer and the decision-making authority for engineering projects. This dissonance often results in engineers being technically accountable for their designs yet lacking the authority to make decisions with respect to the construction, commissioning, and operation of their designs. To address this gap, we suggest leadership and management training be carefully scaffolded in the same manner that technical competence has been stewarded in engineering programs and propose a framework to do so.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.189
Teacher spread0.177 · 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