Assessing the Prevalence of Cross-cultural Competencies in Engineering Design Curricula: A Pilot Study
Bibliographic record
Abstract
With the world becoming increasingly more globalized, cross-cultural competency has become essential for engineering design, especially in the Canadian context. The current paper presents a pilot study aiming to achieve two main objectives: 1) provide preliminary insights into the availability of cross-cultural concepts in engineering design curricula; 2) benchmark against design curricula in other design domains to identify ways that cross-cultural topics can be successfully integrated with engineering design education. The results reveal a general lack of cross-cultural concepts coverage in two sampled engineering programs. From an analysis of two benchmark design programs, three themes are identified that demonstrate how cross-cultural education can be delivered in design courses: 1) culture-related knowledge; 2) reflection on design topics using a cultural perspective; 3) collaboration with cross-cultural teams. The study aims to inspire engineering educators to incorporate cross-cultural concepts into their courses and curricula. This pilot study also helps validate the method for future larger-scale investigations.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".