On using the web as a collaboration space in the context of an industrial simulation
Bibliographic record
Abstract
We present a teaching method aimed at developing higher programming skills from description to production. The model is derived from problem-based learning approaches. It is supported by an "incremental" web site that gradually introduces theoretical presentations, examples, programs and information regarding the problem. The web site is also used as a collaboration space where students can find partial solutions proposed by other teams as well as "requests" submitted by a fictitious client. At the end of the project, each product is published and the best teams are awarded a virtual medal.We had four objectives. The first was to get students to share their expertise and learn to work in teams; second, to teach students the importance of doing a conceptual analysis rather than jumping into programming; third, to introduce theoretical notions, exercises, and examples in class when the students asked for them; and finally, to get students to formulate and describe problems by themselves.Students had to produce a large-scale project that consisted of simulating a factory. The project can be understood at two levels: the first is the problem of developing a discrete simulation of a factory; the second is the creation of the program itself which simulates the industrial context by requiring constant adjustment to new instructions and data.Although this approach requires a lot of effort and coordination on the part of the instructor, the benefits are definitely worthwhile. The model provides students with a broad, in-depth and rewarding learning experience.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".