Embracing Co-Design: A Case Study Examining How Community Partners Became Co-Creators
Bibliographic record
Abstract
Co-design increases the number of voices in a design project, which enhances the experience for all co-creators and produces a better product. A case study is presented of a ten-month co-design project-based learning experience between two engineering design students and two community partners during a first-year engineering design course, which resulted in the implementation of the device across campus. This paper evaluates the elements of co-design in the design process that was employed, documents the design product that was produced, and examines the experience of the community partners through a qualitative study. Through a retrospective examination of artifacts and files, the design process demonstrated an increase in the amount of collaboration between co-creators as the project progressed and identified 15 iterations of the design. Comparing the experience of community partners throughout the design process, five themes emerged from the semi-structured interviews: (1) emotional effects, (2) physical and mental effects, (3) productivity, (4) safety, and (5) job satisfaction. Documenting the experience of community partners throughout the design project can encourage educators to adopt co-design practices in project-based learning.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".