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Record W3000967214 · doi:10.24908/pceea.vi0.13717

AN ENGINEERING DESIGN PROJECT TO PROVIDE MULTI-DISCIPLINARY EXPERIENTIAL LEARNING

2019· article· en· W3000967214 on OpenAlexaffvenue
Seach Chyr Goh, Sumi Siddiqua

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2019
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsExperiential learningProject-based learningSuiteDisciplineEngineering managementEnergy consumptionComputer scienceArchitectural engineeringEngineeringEnvironmental scienceMathematics educationElectrical engineeringGeography

Abstract

fetched live from OpenAlex

First year engineering students at the University of British Columbia Okanagan, take the Fundamentals of Sustainable Engineering Design course as part of the suite of common courses for all engineering students regardless of discipline. The largest assessment components of the course are the final exam (40%) and the design project (40%). For the design project, teams of 4 – 6 students build a scaled-down prototype of a Well Ventilated yet Energy Efficient Room (WeVeyEER) that must be able to maintain its interior temperature at 10°C above ambient and at the same time continuously exchange stale air from within with fresh air from outside. It also has to meet load-bearing, size and power supply constraints. The energy consumption, rate of air exchange and weight are parameters for comparing performance of the prototypes. The majority of teams (55 out of 64) could achieve the requirements. Feedback about the project was mixed, with 57 positive and 56 negative comments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0360.011

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2019
Admission routes2
Has abstractyes

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Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicEngineering Education and PedagogyFrench-language works237,207