Creating an Escape Room: A Discussion on Experiential Learning and Interdisciplinary Studies
Bibliographic record
Abstract
The institution of the university is changing rapidly. No longer are students attending university to simply become experts in an area of interest. Instead, students are expecting to graduate university with enough experience to enable their professional careers and futures. In recent years, Brock University has been using ‘experience’ as a tag line to market itself: “EXPERIENCE. EDUCATION.” “EXPERIENCE. HOMECOMING.” “EXPERIENCE. DRAMATIC ARTS.” This choice was made to emphasize the university’s belief in experiential learning. In 2017, third-year students from Brock University’s Department of Dramatic Arts and Department of Interactive Arts and Science practised experiential learning by collaborating with the Niagara Military Museum to build fully functional escape rooms. Utilizing the skills developed in their programs, the students accomplished an impossible task and created a World War I escape room and a Cold War-themed escape room for beta testing. A unique experience for all involved, it is rare that at a university, students from different majors would collaborate at all, let alone with a task involving such high stakes. This article features a raw, candid conversation between students involved in this process.
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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 | 0.034 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.019 | 0.050 |
| Scholarly communication | 0.022 | 0.023 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".