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Record W1937595908 · doi:10.24908/pceea.v0i0.5945

Comparative Analysis of Engineering Curricula for Alignment with 21st Century Engineering Practices

2015· article· en· W1937595908 on OpenAlexaffvenueabout
Anita Lazurko, Patrick B. Miller, Dena Ghoneim

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsEngineers Without Borders Canada
FundersUniversity of Tokyo
KeywordsCurriculumEngineering educationInfluencer marketingEngineering ethicsGlobalizationWork (physics)EngineeringPosition (finance)Engineering managementPolitical scienceSociologyPedagogyManagementMechanical engineeringBusiness

Abstract

fetched live from OpenAlex

The vast engineering challenges of the 21st century and the unique position of engineers as decision makers, conveners, and influencers has created a need for a directional shift in the content and teaching methods used in Canadian engineering education.Both Canadian and international universities were evaluated based on nine criteria deemed relevant and important to the evolution of engineering education by Engineers Without Borders Canada. These include overall vision and direction of the engineering faculty and university, interdisciplinary opportunities, leadership programs and recognition, topics in technology and society, innovation in curriculum content or delivery, a growing understanding of globalization, cross cultural communication and project management, and a direct connection between work experience and curriculum.Results have shown that many Canadian universities are strong overall, while some universities have strengths in a few areas. These results can be utilized and shared as best practices. The international program evaluation showed very diverse results, some of which can be adapted and utilized in Canadian engineering curriculum. These results can be employed as many entities collectively move forward to develop and reinvent engineering education in the 21st century.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
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
Bibliometrics0.0010.002
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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations1
Published2015
Admission routes3
Has abstractyes

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