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Record W2887990344 · doi:10.24908/pceea.v0i0.7368

Engineering the Future: A Conceptual Framework for Evolving Engineering Education

2017· article· en· W2887990344 on OpenAlexaffvenue
Kai Zhuang, Franc Newland

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2017
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsYork University
Fundersnot available
KeywordsIngenuityAgency (philosophy)Engineering ethicsContext (archaeology)Work (physics)Perspective (graphical)Engineering educationEngineeringEngineering managementSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Today, we live in a world of unprecedented challenges, opportunities, and complexities, where advances in technology are transforming the very fabric of our culture, economy, and environment. Engineering education is responsible for preparing students for the unprecedented challenges, opportunities, and complexities of this emerging future. Here, we share our current perspective on the evolution needed in engineering education via a conceptual model we have developed. In particular, we highlight the need for engineers to engage in social agency over technology, which requires them to understand the social context in which they live and work, and explore the kind of ingenuity needed to create a future where technology meets society’s need. We use the model to analyze a number of educational initiatives we have developed at the Lassonde School of Engineering.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 designNot applicable
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
Published2017
Admission routes2
Has abstractyes

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