<i>Future delta 2.0</i> an experiential learning context for a serious game about local climate change
Bibliographic record
Abstract
In this paper we discuss the theoretical, design and evaluative underpinnings of the experiential learning context central to the design processes of the Future Delta 2.0 serious game. The game is aimed at facilitating understanding and action on local climate change. We begin with a discussion of play as it relates to designing serious games. Then we articulate the experiential learning context revealed through three interconnected design strands: meaningful learning objectives -- how the learning is structured; situatedness -- where the learning takes place, geographically and culturally; learning through action -- how learning happens through play. We introduce the experiential learning context of Future Delta 2.0, a virtual 3D game. The game reaches across art, science and technology to communicate a community-based local vision of climate change challenges and solutions in Delta, British Columbia. Finally, we discuss the design, evaluation methods and analysis of the Future Delta 2.0 experiential learning context. Our conclusion is that the experiential learning context may contribute theoretically and practically to the research and design of 3D serious games.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".