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Record W2598939629 · doi:10.18260/1-2--11202

Design Projects In The Mechanical Engineering Curriculum At Sherbrooke University Past, Present, And Future

2020· article· en· W2598939629 on OpenAlexaffabout
Y. Mercadier, Pierre Vittecoq, Patrik Doucet, Jean‐Sébastien Plante, François Charron, Yves Van Hoenacker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCurriculumEngineeringEngineering managementEngineering design processPlan (archaeology)Work (physics)Session (web analytics)Engineering educationEngineering ethicsMechanical engineeringComputer sciencePedagogySociologyGeographyWorld Wide Web

Abstract

fetched live from OpenAlex

Since 1992, students in our undergraduate mechanical engineering program have been carrying out major design projects.The process of integrating major design project activities was spread over three phases.The first phase, which took place between 1992 and 1994, consisted of a pilot program with forty students.The implementation of an engineering design option between 1995 and 1999 constituted the second phase.The last phase embraced the complete reform of the undergraduate curriculum based on the development of competencies and the horizontal/vertical integration of engineering sciences and engineering design.One of the principal objectives of the major design projects is to allow the students to live a major design experience within the undergraduate curriculum.The students work on the same project during the last four terms of their program (more than two calendar years as a result of the work terms).They receive 12 credits for their design project work.This paper presents our ten years of experience in using design projects as a tool for teaching engineering design.It also sets out our development plan for teaching engineering design over the next five years.NSERC (National Sciences and Engineering Research Council of Canada) Engineering Design Chair will support these future developments. ENGINEERING DESIGN PROJECTS 1992 to 1994 -Pilot Program in Engineering DesignFollowing a literature review on the use of design projects as a tool for teaching engineering design in other universities and an assessment of the scale of the work required for introducing major design projects in our program, our department decided to start with a pilot program.The principal advantage of this approach was the state of mind of the project stakeholders (professors Page 7.376.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.002
Scholarly communication0.0050.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0250.005

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 head0.013
GPT teacher head0.183
Teacher spread0.170 · 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 designQualitative
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".

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Citations4
Published2020
Admission routes2
Has abstractyes

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