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Record W2909909822 · doi:10.24908/pceea.v0i0.13096

A Cornerstone Design Module in First Year Engineering

2018· article· en· W2909909822 on OpenAlexafffundvenue
Peter Ostafichuk, David Sommer, Carol P. Jaeger

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsCornerstonePresentation (obstetrics)StakeholderEngineering design processComputer scienceWorkloadRelevance (law)Event (particle physics)Flexibility (engineering)Engineering managementSystems engineeringEngineeringSoftware engineeringSimulationMechanical engineering

Abstract

fetched live from OpenAlex

This paper describes a new five-week cornerstone design module at the conclusion of first year engineering at the University of British Columbia (UBC).The objective of this cornerstone module is to bringtogether the multiple course themes—developed over the preceding six modules and 18 academic weeks—into a single, integrative and culminating experience. The module builds on the previous course topics, andspecifically emphasizes design, stakeholder consultation, prototyping, sustainability, and communication in a unified project experience. Through a mix of analytical and physical prototyping, teams design a pilot rainwater harvester system for small, remote communities. Teams specify the system components in their design, and submit those through an online form. All systems are then simulated off-line in a detailed MATLAB model that tracks weather, physical performance, cost, maintenance, healthand safety risks, and more. The culminating event for the module is a formal oral presentation followed by a timelapse video of the simulations of the different teams’ rainwater harvester system designs.The outcomes to the module have been very positive.The module has successfully run for three years with over 400 teams. Feedback through surveys shows students find the cornerstone project meaningful and helpful in developing their ability to use simulation and numerical modelling in design. Students have also rated the module highly in terms of the relevance to their degree, and the importance of the learning outcomes to engineers.Primary challenges noted to date include inequities instudent workload within a team, due to shifting priorities as final exams approach, and ability to update the project each year to maintain a new challenge for each cohort.

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)0.003
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0030.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1250.057

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 head0.009
GPT teacher head0.202
Teacher spread0.192 · 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
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
Published2018
Admission routes3
Has abstractyes

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