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Record W1824038691 · doi:10.24908/pceea.v0i0.4652

QUESTIONNAIRE FOR ASSESSING DESIGN PRACTICES

2012· article· en· W1824038691 on OpenAlexaffvenueabout
Steeve Gendron, Jean Brousseau, Abderrazak Elouafi, Bruno Urli

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2012
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsDimension (graph theory)Process (computing)Product (mathematics)Knowledge managementQuestionnaireProcess managementExploratory researchComputer scienceEngineering managementEngineeringMathematics

Abstract

fetched live from OpenAlex

In 2010, an exploratory survey on methods, tools and design techniques (MTT) has led to a better understanding of design practices of small and medium enterprises (SMEs) located in Eastern Quebec. The results of this survey have shown that most companies report having a structured design process, while only some resort to MTT. Following this study, a new research was launched to develop performance indicators for the design process, but also, and more generally, for design projects. To do this, a tool was developed to characterize and evaluate the design practices of companies as a way to establish performance indicators following a longitudinal study. A questionnaire was developed as a tool based on a model of design system consisting of six dimensions (human, management, environment, product, process and techno-scientific). In the questionnaire, each dimension is characterized by different descriptors which are analyzed by four aspects that measure: i) if the descriptors are taken into consideration (the occurrence of the descriptors), ii) the importance of the descriptors according to the project success , iii) the company’s performance level related on the descriptors and iv) the involvement of partners. For validation purposes, the tool was tested on a pilot basis by eight companies. This paper introduces the questionnaire and the model that directed its construction and the types of analysis that can be conducted using the data collected.

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)0.005
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 score0.387
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.272
Teacher spread0.248 · 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

Citations1
Published2012
Admission routes3
Has abstractyes

Explore more

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