A Serious Game Proposal for Raising Awareness on Sustainable Development in the Built Environment
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
Interactive serious games enhance science-based communication and promote deeper learning about sustainable development. It is yet undiscovered that how can AI-augmented interactive experiences enhance the engagement and spread awareness. This study proposes an AI-augmented digital serious game in public installation format. First, the study introduces a serious board game centered on Sustainable Development Goal (SDG) 11 to test the learning aspects and the engagement of the game. The study hypothesizes that a serious game with a clear message, engaging mechanics, and appealing design can significantly enhance understanding of sustainability’s relevance to everyday life. Using a Research through Design (RtD) approach, the study incorporated iterative feedback from pilot tests. These tests highlighted the effectiveness of problem-solving and group discussions in fostering engagement. The insights directly informed the design of the digital version, which emphasizes streamlined and accessible gameplay.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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