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Record W4308713589 · doi:10.24908/pceea.vi.15972

Sustainable Systems Engineering Course Design: Design for Systems and Society

2022· article· en· W4308713589 on OpenAlexaffvenueabout
R. Paul, Marjan Eggermont

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMindsetEngineering ethicsSustainabilityTransformative learningPraxisEngineering managementDesign educationEngineeringEngineering educationCurriculumEngineering design processSociologyComputer sciencePolitical sciencePedagogyBusiness

Abstract

fetched live from OpenAlex

The new Sustainable Systems Engineering program at the University of Calgary aims to disrupt sustainability education by imbedding a systems approach and regenerative design mindset throughout. This paper provides an overview of a second-year design course, SUSE 301, Design for Systems and Society. The course introduces students to concepts of design for circular economy, regenerative design, and design for justice. Underlying all of these concepts is the idea of transformative learning through a systems thinking approach. Course assignments include chapter studies and discussions, critical reflection through a praxis experiment, and community-engaged design project. Overall, we hope to foster mindsets to develop engineering students who are able to fundamentally shift the discourse on sustainability engineering within industry, and critically reflect on the role of engineering itself. This course aims to provide students with the necessary tools and mindsets to foster real change across engineering industries to better support the interrelated elements of our society and planet.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.249
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes3
Has abstractyes

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