MétaCan
Menu
Back to cohort
Record W1909573471 · doi:10.24908/pceea.v0i0.3720

THE CHAIR PROJECT: FIRMNESS, COMMODITY, AND AN EMPHASIS ON DELIGHT

2011· article· en· W1909573471 on OpenAlexvenueno aff
Elizabeth English

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsCourseworkConstruct (python library)Computer scienceArchitectureFolding (DSP implementation)CurriculumObject (grammar)Mathematics educationSoftware engineeringEngineering managementEngineeringPsychologyPedagogyArtificial intelligenceVisual artsArtProgramming language

Abstract

fetched live from OpenAlex

This paper will describe the theoretical approach and methodology and show the outcome of a pedagogical experiment that has proven to be highly successful in motivating architecture students to master structural analysis and design. The Chair Project is the term project for the last of the sequence of three required Structures courses in the curriculum of the University of Waterloo School of Architecture. Each student is required to design, construct and structurally analyze a folding or take-apart wooden chair for a specific "client". The choice of his/her client is up to the student, but should be a well-known creative personality who can serve as a term-long inspiration for the design of the chair. By being assigned a small but structurally provocative design-build project as part of their structures coursework, the students are provided with an immediate need-to-know application while they are learning the techniques of structural analysis. The folding wooden chair as a design-build and computational analysis project has the additional benefit of being an object that the students are able to construct, analyze and load-test at full scale.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.018
GPT teacher head0.229
Teacher spread0.211 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicDesign Education and PracticeFrench-language works237,207