Bibliographic record
Abstract
In this paper we present how students at an arts immersion school in Canada, designed games using Minecraft as a design tool to represent Grade 8 curriculum content learnt in Social Studies. Our research was based on our theoretical framework on how game design could be an aesthetic process, which elaborates how a design commences with a problem and progresses as an iterative creative cycle towards finding a solution. Using this framework, we examined two groups of Grade 8 students’ game design process. The groups represent unique approaches towards problem solving that incorporated content from the Aztec and Spanish Civilization in their game design. We have interpreted the representation of the content as the posed problem and analyzed how each group proceeded with their game making based on their ideas, experience at playing the game and feedback received from fellow classmates. Our findings highlight how the design process through Minecraft was a creative endeavour on their part. Through our findings, we re-emphasize how involving students in game creation efforts help them to experience an aesthetic learning process, allowing them to become protagonists of their learning. We argue for game design as learners’ problem solving experience, through which they struggled to construct knowledge in social systems while developing fluencies both in gaming and technology.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.015 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".