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Record W2145989953 · doi:10.24908/pceea.v0i0.4027

MENTOR-MANAGED DESIGN CHALLENGES FOR FIRST YEAR ENGINEERING

2011· article· en· W2145989953 on OpenAlexaffvenue
Carolyn MacGregor, Linda Carson

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDeliverableScope (computer science)UsabilityStructuringEngineering managementComputer scienceSystems engineeringKey (lock)EngineeringEngineering design processDesign elements and principlesSoftware engineeringConstruction engineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

The authors identify the main challenges facing engineering students and instructors during hands-on design projects and give an overview of the mentor-managed approach they take in a first year design course. Key features of the course include mentor management, choosing a design challenge of a suitable scope, providing an appropriate systematic design methodology, and structuring the design project around staged deliverables. They describe, in more detail, two distinctive components of the course: usability testing with modified design walkthroughs, and an introduction to creative practice and design through a Scrapheap Challenge.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.203
Teacher spread0.173 · 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 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

Citations2
Published2011
Admission routes2
Has abstractyes

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