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Record W4403794140 · doi:10.24908/pceea.2023.17006

Instilling SDG Considerations in Undergraduate Design Capstone

2024· article· en· W4403794140 on OpenAlexafffundvenueabout
Tate Cao

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsCapstoneEngineering ethicsMathematics educationComputer scienceEngineeringPsychologyComputer security

Abstract

fetched live from OpenAlex

Engineering education in universities often focuses on theoretical problems, with limited opportunities for students to consider the societal and environmental impact of their designs. Senior engineering design capstones typically involve industry partners providing the problem and context, further restricting students' ability to explore implications. Despite being aware of the United Nations Sustainable Development Goals (SDGs), students prioritize personal over professional implications. This study aims to incorporate SDGs into the Engineering Capstone experience by introducing them in a senior student-driven, multidisciplinary Engineering Capstone Design class. Students receive empathy training and use Canadian indicators of UN SDGs to align their designs with positive and negative indicators. They engage with users for feedback on the impact of their choices on SDGs, bridging the "blind spot" in their design work and enhancing understanding of the broader context of their designs. Incorporating empathy training and a co-design approach can improve students' understanding of the potential impact of their designs on SDGs.

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)0.001
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 score0.458
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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

Citations1
Published2024
Admission routes4
Has abstractyes

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