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 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 | 0.001 |
| 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".