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Record W1887604739 · doi:10.24908/pceea.v0i0.3901

A FINAL YEAR DESIGN COURSE BASED ON INDUSTRY DERIVED PROJECTS

2011· article· en· W1887604739 on OpenAlexaffvenue
Greg Schoenau

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBrainstormingGraduation (instrument)Presentation (obstetrics)Course (navigation)Engineering managementWork (physics)Process (computing)Quality (philosophy)Function (biology)Focus groupEngineering design processEngineeringMathematics educationComputer sciencePsychologyMarketingBusiness

Abstract

fetched live from OpenAlex

This paper describes a two term design projects course in the Mechanical Eng. Dept. at the U of S. It is considered to be a “flagship” course for students in the final year of their program. Students focus on solving design problems submitted by industries and other outside organizations. Each student group works on a separate and unique project. The course provides students with an excellent opportunity to apply their engineering analysis and design theory. They function as a team, typical of practicing consulting engineers. They are responsible for the direction and quality of the work performed. Faculty act as technical advisors to the students, not as supervisors. The student groups search the literature, brainstorm design alternatives and analyze and test promising alternatives. A final report and seminar presentation are required for every group as well as periodic progress reports and presentations. Students get to work on a “real world” problem, typical of exactly what they might experience after graduation. This is really an extremely important and crucial distinguishing feature of the course and serves as a strong motivator for the students. The course therefore acts as a bridge between a student’s academic training and their practice of engineering. For industry, it is an opportunity to investigate the feasibility of a new design, process or method of production for minimal cost.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.200
Teacher spread0.178 · 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 designObservational
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

Citations2
Published2011
Admission routes2
Has abstractyes

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