DEVELOPING A MODEL FOR INNOVATION IN UNDERGRADUATE ENGINEERING EDUCATION – THE SYSTEMATIC INTEGRATION OF HUMAN-CENTERED DESIGN
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The goal of this project was to integratemore human factors and human centered design contentinto mechanical engineering courses. Using the Six Sigma(DMAIC) approach, we defined HF broadly as anycourse content aspects related to humans. We measuredthe HF content of courses based on interviews with 38instructors. All but six courses had less than 10 hours ofHF content and only one course taught students how touse HF aspects to improve design. Twelve courses weretargeted for improvement and of these, seven instructorsagreed to integrate HF content. The observed rate ofchange is modest and ongoing support would be neededto foster more substantial development. We recommend amore nuanced 4-level model for defining HF-relatedcoursework. We also discuss the barriers to integratingHF and suggest some countermeasures
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it