Architect-Client Communication During Co-ideation with 2D Digital and 3D Immersive Sketches
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.
Bibliographic record
Abstract
Effective architect-client communication is crucial for the successful progress of the design process. Traditional 2D sketches may pose challenges due to the high uncertainty experienced by clients regarding the project. This kind of communication is perceived as the intersection of clarity of information, clarity of sketched representations, and suitable communication methods (verbal and non-verbal). Aiming to support it, this case study evaluates the level of uncertainty and clarity experienced by architects and clients when using 2D digital sketches and immersive 3D sketches during co-ideation. This case study followed an architect and two clients co-ideating two similar small projects, using three digital sketching tools: 3D sketches on Gravity Sketch using Oculus Quest 2 VR headsets, Hyve-3D co-design immersive projection system (VR without headsets), and 2D sketches with a digital tablet using its pen. Each project included three twenty-minute sessions per tool, followed by a questionnaire. Preliminary findings suggest that 3D sketches offer better clarity and reduce participants' uncertainty. We found generally high expectations from the tools at the beginning of the collaborative sessions and a subsequent decrease in impressions at the end due to the lack of clarity of the proposed representations. The immersive projection system better supported non-verbal communication, observed through gestures, whereas the VR headset restricted this activity.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it