Implementing Game Design in School: A Working Example | Mise en œuvre de la conception de jeu à l’école : un exemple pratique
Bibliographic record
Abstract
This case uses a worked or “working example” model (Gee, 2010), documenting the implementation of a novel game design curriculum in the United States. Created by an Instructional Technology Administrator (ITA) and two classroom teachers, it was subsequently offered to high school students. With an aim of providing in-depth understanding of conditions necessary to bring game design experiences to classrooms, the research describes the context while revealing processes and instructor perceptions of the experience. Data collection and analysis in this working example include observation, teacher interviews, student surveys, and artifacts intended to make thinking and practices overt while inviting scholarly conversation around the curriculum’s successes and failures. Drawing on a previous case focused on initial course planning and early implementation (Author, 2013), this paper advances insight regarding the process of moving game design into schooling and concludes with a discussion of educational implications. Cette étude se sert d’un modèle « d’exemple concret » (Gee, 2010) pour documenter la mise en œuvre d’un programme de conception de jeu aux États-Unis. Créé par un technopédagogue et deux titulaires de classe, le programme a ensuite été offert à des élèves du secondaire. Visant à fournir une compréhension approfondie des conditions requises pour l’intégration des expériences de conception de jeu en classe, l’étude décrit le contexte et révèle les processus et les perceptions qu’a tirés l’instructeur de l’expérience. La collecte de données et l’analyse dans cet exemple concret comprennent l’observation, des entrevues avec les enseignants, des sondages auprès des élèves et des artefacts ayant pour but de rendre manifestes la réflexion et les pratiques tout en stimulant la conversation savante à propos des réussites et des échecs du programme. S’appuyant sur une étude préalable qui mettait l’accent sur la planification initiale du cours et le début de sa mise en œuvre (Herro, 2013), cet article propose une perspective sur le processus d’intégration de la conception de jeu dans la formation et conclut avec une discussion portant sur les répercussions pédagogiques.
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 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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".