Bibliographic record
Abstract
This paper describes a studio model that attempts to bridge the gap between conventional design studio settings and professional practice, by adopting design-build principles that incorporate experiential learning theory, derived from the early research of Dewey, Lewin, and Piaget. Part of the dichotomy of the profession is the dynamic difference in the established representational tools of the trade and the result of the built environment. This disconnect exists because the tools of the trade utilize two dimensional explanations about a three dimensional place, typically comprised of drawings in the form of plans, elevations, and perspectives. Additionally, there is a dynamic difference in scale that exists between these tools and the environments they represent. Thus, design educators tend to teach representational techniques without teaching a clear understanding of what they represent. This gap in education creates a gap in the profession. The described case studies outline an alternative studio model that is intended to introduce some of the “realities” often missing in a conventional studio approach. Each of the case studies involved second year Interior Design students, who were given the parameters of an existing space with specific user needs. The students had to design and then physically construct that interior environment all within a ten week time period (one academic quarter). By creating a more “hands-on” learning environment, it is the hope that students retain that knowledge in a more meaningful and lasting way, with the ability to transfer that experience over to similar situations in other studio settings and within the professional practice.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".