Exploring the Effect of Immersive VR on Student-Tutor Communication in Architecture Design Crits
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
Using digital tools like immersive Virtual Reality (iVR) reduce the carbon footprint by providing collocated and remote communication through virtual design studios. By providing a sense of presence in a digital display, iVR systems impact student-tutor communication during design critiques or crits. Research lacks studies articulating how iVRs change crits' communication to increase the ability to integrate iVRs as educational media and promote a quality education in inter-university studios. To this end, this study explores the cognitive structure of student-tutor communication during collocated architecture crits using iVR and non-immersive media. We employed protocol analysis to analyze divergent thinking by tracking the distribution of First Occurrences of design issues. Combining protocol analysis with Natural Language Processing, we explored the size of the design space generated during the crits. Results from a case study that includes twelve crits from three students show an increase in students exploration of the design space and divergent thinking in the iVR crits, providing evidence that iVR enhances learners' communication. iVRs can be integrated to support remote design studios without the generation of carbon due to physical travel.
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 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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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