Optional CDIO Standards: Sustainable development, Simulation-based mathematics, Engineering entrepreneurship, Internationalisation & mobility
Bibliographic record
Abstract
An effort to update the CDIO Standards from version 2.1 to 3.0 was started in 2017 (Malmqvist et al., 2017) and further outlined in 2019 (Malmqvist et at., 2019). The aims were to incorporate external changes to the context of engineering education, to address criticism that had been raised against earlier versions of the standards, and to establish an extendable CDIO framework architecture. The work has resulted in that the original twelve CDIO standards, from now on named “core” CDIO standards, will be complemented by "optional" CDIO standards, that codify additional educational best practices that have been developed within the CDIO community in the same format as the original CDIO standards. Eleven optional standards have been proposed (Malmqvist et al., 2019). This paper accounts for the elaboration of the subset of the proposed optional standards that were recommended for further development by the CDIO Council in November 2019. These recommended optional standards are presented as full texts, i.e., including descriptions, rationale and rubrics. The described optional standards are: Sustainable development, Simulation-based mathematics, Engineering entrepreneurship and Internationalization and mobility
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.016 |
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".