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Record W2612530002 · doi:10.21606/drs.2016.284

Exploring framing within a team of industrial design students

2016· article· en· W2612530002 on OpenAlexaff
Mthra Zahedi

Bibliographic record

VenueProceedings of DRS · 2016
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCognitive reframingFraming (construction)Co-designCollaborative designParticipatory designIndustrial designComputer scienceEngineeringKnowledge managementPsychologySocial psychologySystems engineeringTask (project management)

Abstract

fetched live from OpenAlex

How do ideas evolve in the context of collaborative design? This research explores the framing strategies and tools involved in the co-construction of a shared understanding in the early stages of a design project. We observed a team of four industrial design students working to design a popup shop. We found that, while the key design elements of the solution were present from the early stages of discussion, they were continually framed and reframed through intense verbal discussion supported by sketching reflection-in-action (individual or collective) that help each team member make sense about the popup shop branding, user experience, visibility, structure, etc. The design ideas were crystallized at the end of the fourth working session. The research presents the cycle of framing and reframing of ideas that emerged from different symbolic elements associated with a brand, allowing students to design customized, non-standard, impressive and complex forms.

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)0.017
metaresearch head score (Gemma)0.033
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.001
Science and technology studies0.0120.015
Scholarly communication0.0180.007
Open science0.0030.013
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.170
GPT teacher head0.289
Teacher spread0.118 · 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".

Quick stats

Citations6
Published2016
Admission routes1
Has abstractyes

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