Playing for Climate Change: The Design and Development of a Game Prototype to Promote Scientific Literacy
Bibliographic record
Abstract
This design case describes the work involved in developing a digital game-based learning environment, work that was part of a PhD research project. The designer was involved in all aspects of the project: conducting research into content that was included in the game, exploring the gaming platform (Second Life), adapting scientific literature for use in the game, consulting with science instructors, building the gaming environment, and writing scripts for objects in the environment. The gaming environment was a fictional town site called Budworm. The game was designed to promote scientific literacy in first and second year science undergraduate students through collaborative work on an open-ended problem related to the management of water resources in a region of western Canada subject to extremes in water availability. One of the design goals was to model the kind of environment that scientists encounter while they formulate research questions, a complex environment that involves collaboration with colleagues, creativity and a willingness to explore. Instructional experts in three scientific fields (biology, chemistry, and geosciences) were consulted during the course of this design, as was an expert in instructional design. The final product was the game and a set of game design principles that were informed by the literature on educational gaming and consultations with the instructional experts.
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.
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 | 0.001 | 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 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".