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Record W2110183716 · doi:10.1177/0739456x12455065

Experiential Learning and the Co-creation of Design Artifacts

2012· article· en· W2110183716 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Planning Education and Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaUniversity of Utah
KeywordsExperiential learningStudioArtifact (error)Design studioLearning designReading (process)Visual artsLiteracyPedagogyMathematics educationComputer sciencePsychologyArtLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

This article examines the experience of a hybrid design studio tailored for beginning students in urban planning. The course combined elements of architectural design studio and planning workshop to advance design literacy, spatial awareness, procedural knowledge, and phenomenological experience. Teams of students undertook staggered weekly sequences of reading, critique, and design assignments focused on physical models of study neighborhoods. Through content analysis of student work, documentary film footage, and postgraduation surveys, I examine the merits of the hybrid studio. The co-creation of a model, which was an iterative and dialogically tested design artifact, heightened experiential learning of urban design.

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.

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)0.010
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.336
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.148
GPT teacher head0.575
Teacher spread0.427 · 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