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Record W1917072110 · doi:10.24908/pceea.v0i0.3745

AN INDUSTRIAL DESIGN-ORIENTED ENGINEERING ECONOMICS COURSE

2011· article· en· W1917072110 on OpenAlexafffundvenue
Haytham Elmiligi, Scott C. Iverson

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Victoria
FundersUniversity of Victoria
KeywordsDocumentationEngineering managementProject-based learningComputer scienceEngineering economicsProject managementWork breakdown structureProject planningManagement scienceSoftware engineeringProject charterSystems engineeringEngineeringMathematics educationBusiness

Abstract

fetched live from OpenAlex

This paper presents techniques and methods to improve engineering students’ design skills through a project- based course. We developed a well-defined project to engage second year students in an authentic industrial design flow. This flow starts by studying the feasibility of a target project and progresses to the selection of the best alternative using various financial analyses. It then evaluates the project’s potential success rate using pre-defined evaluation criteria. This project is implemented through the concurrent application of the textbook’s theoretical concepts of engineering economics. By applying the project, we fill the gap between academic theoretical concepts and the industrial real-life design and creation of products. Finally, we prepared a professional document that explains the specifications, requirements, and guidelines of the project. It also helps students in choosing the proper topic of their project, in exploring different project alternatives, and in preparing appropriate project documentation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

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 head0.014
GPT teacher head0.183
Teacher spread0.169 · 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.

Study designSimulation or modeling
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

Citations0
Published2011
Admission routes3
Has abstractyes

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