The co.LAB Generic Framework for Collaborative Design of Serious Games: Development Study
Bibliographic record
Abstract
BACKGROUND: Serious games are increasingly used at all levels of education. However, research shows that serious games do not always fulfill all the targeted pedagogical objectives. Designing efficient and engaging serious games is a difficult and multidisciplinary process that requires a collaborative approach. Many design frameworks have been described, most of which are dedicated to the development of specific types of serious games and take the collaborative dimension into account only to a limited extent. OBJECTIVE: Our aim was to create a generic serious game design framework that could be adapted to all kinds of serious games and implemented in a collaborative web platform. METHODS: We combined the results of a literature review with our experience in serious game design and development to determine the basic building blocks of a collaborative design framework. We then organized these building blocks into categories and determined the features that a generic design framework should include. Finally, based on the paradigm of complex systems and systemic modelling, we created the co.LAB generic design framework and specifications to allow its implementation in a collaborative web platform. RESULTS: Based on a total of 10 existing design methodologies or frameworks, 23 building blocks were identified and represent the foundation of the co.LAB framework. These blocks were organized into 5 categories: "context and objectives," "game design," "mechanics," "learning design," and "assessment." The arrangement by categories provides a structure that can be visualized in multiple and complementary ways. The classical view links game and learning design while other views offer project, systemic, and process visualizations. For the implementation of the co.LAB framework in a web platform, we propose to convert the building blocks into "cards." Each card would constitute a collaborative working space for the design of the corresponding block. To make the framework adaptive, cards could be added, adapted, or removed according to the kind of serious game intended. Enhancing the visualization of relationships between cards should support a systemic implementation of the framework. CONCLUSIONS: By offering a structured view of the fundamental design elements required to create serious games, the co.LAB framework can facilitate the design and development of such games by virtue of a collaborative, adaptive, and systemic approach. The different visualizations of the building blocks should allow for a shared understanding and a consistent approach throughout the design and development process. The implementation of the co.LAB framework in a collaborative web platform should now be performed and its actual usability and effectiveness tested.
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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 | 0.001 |
| 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".