Design and Engineering: A Classification and Commentary
Bibliographic record
Abstract
There are myriad understandings of design that have evolved over time and vary by the industries and disciplines that practice it. In the engineering context, design is often described as a process or problem-solving ability. Through interviews with 12 experienced engineers, it was found that there are diverse understandings of the relationship between design and engineering. This qualitative study presented a classification of their perspectives through three emergent categories: the relationship between design and engineering, the proportion of design tasks within a job, and the level or stage of development where design occurs. A synthesis of the data revealed that engineers demonstrate an ownership of design within engineering and there are diverse understandings of how design occurs within engineering. The implications of these findings were discussed and recommendations were offered for engineering educators, researchers, and industry. Engineering educators can help prepare designers as catalysts to produce a more inclusive, holistic, and sustainably minded profession.
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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 | 0.028 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.012 | 0.037 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.021 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".