Playing And Learning Without Borders: A Real-time Online Play Environment
Bibliographic record
Abstract
ENJEUX-S is a development/research project financed by the AAP program (Industry Canada) from November 2004 to November 2006. Its objectives are to develop and validate an advanced games and simulations environment, based on a Web Services and telecommunications architecture to support the development and experimental activities of the generic game and simulation shells of the SAGE portal. This environment will support multi-user functions by means of transactional and interpersonal types of interactivity. Relying on a Web Services model, the environment will allow real-time interaction (digital telephony or videoconferencing) and animation (video, voice, sound, graphics or images). This advanced environment will provide transparent support for games and simulations developed by means of the generic shells implemented in the SSHRC-INE project. The core of the ENJEUX-S project integrates the components of real-time communication in the domain of Internet-based educational games and simulations. This integration - one of the original aspects of this project - enables the utilisation of enhanced educational situations (feedback, on-line dialogue, immediate assistance, shared strategies, help, etc.), where the real world meets the virtual world so as to investigate simple or complex 2-D or 3-D learning situations. On the one hand, the addition of multimedia components to educational games and simulation interfaces (interactivity) and, on the other hand, the instantaneous and simultaneous interactions provided by the proposed architecture, allow the handling of educational situations where geographically dispersed users will be able to act together, make concurrent decisions and cooperate among themselves all in real-time, thus emphasizing the emotional, communicative and social potential of educational situations. In summary, the environment developed in the ENJEUX-S project aims at developing user-friendly, on-line training situations, based on dialogue and intervention in teleconferencing mode (virtual face-to-face). This workshop will first present the design stages underlying the development of this environment, followed by examples of the operation of the environment using games and simulations developed within the SAGE project. Finally, participants will be invited to comment on the proposed environment with respect to their training requirements.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".