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Record W2909128751 · doi:10.24908/pceea.v0i0.13045

Alumni Perspective on their Undergraduate Engineering Leadership Experience and Important Career Skills

2018· article· en· W2909128751 on OpenAlexaffvenue
R. Paul, Lynne Cowe Falls

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHumilityPerspective (graphical)EmpathyThematic analysisCuriosityLeadership studiesGraduate studentsPsychologyPedagogyEngineering ethicsLeadership developmentMedical educationSociologyQualitative researchPolitical sciencePublic relationsEngineeringLeadership styleComputer scienceSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Engineering leadership is increasingly recognized as an essential attribute for engineers as they enter the dynamic and complex modern workplace. Increasingly, undergraduate institutions are offering leadership development to their engineering students. The question then follows, as these student leaders graduate and go into their career, did their student leadership experiences help to equip them to be successful in their career? This paper presents the results from a thematic analysis of twelve interviews with alumni student leaders. The results showed that the most influential factors of student leadership were: humility, empathy, and curiosity.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
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 science0.0000.000
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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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 teacher head, not a consensus.

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

Citations3
Published2018
Admission routes2
Has abstractyes

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