Integrating Stakeholder Interactions into First-Year Design Courses: Perceived Value & Impact on Students
Bibliographic record
Abstract
Incorporating stakeholders into engineering design courses is important but challenging. A case-study-based approach of integrating stakeholder interactions into first-year engineering design courses was studied with the hypothesis that students would see value in stakeholder interactions. First-year students in two programs, Systems Design Engineering (SYDE, n=120) and Biomedical Engineering (BME, n=100), completed a beginning and end of term survey to understand their perceptions of stakeholder interactions in their first-semester engineering design course. The vast majority (96 to 98%) of students indicated that stakeholder interactions should persist in first-semester engineering design courses. Both cohorts placed high importance on stakeholders as an information source. However, BME students placed higher value in stakeholder interactions than their SYDE peers. This may relate to stakeholder alignment and interaction modality. While stakeholder interactions were effectively integrated into these courses, future work includes assessing effectiveness in different cohorts and developing a program-level plan for advancing stakeholder interactions.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".