Engineering Students as Responsible Innovation Auditors? An Intervention in Engineering Design Pedagogy
Bibliographic record
Abstract
Responsible Innovation (RI), which was once a concept exclusive to academic research, has gained popularity in the past decade in corporate, governmental, and non-profit sectors. Some educators have responded by integrating RI into engineering classrooms. This paper describes a semester-long assignment in which first-year Electrical and Computing Engineering students in a mandatory communication course roleplay as Responsible Innovation Auditors for peers in a first-year engineering design course. The assignment asks students to understand and apply RI concepts in a real-world scenario, addressing their peers as clients in need of RI consultation. While gaining skills in engineering communication, students are taught the basic premises of RI, apply these concepts to the systems-mapping of a client project, and produce a detailed recommendation report based on the principles of RI. The goal of this intervention is to introduce RI early in the engineering curriculum to promote technological stewardship and foster the grass-roots expansion of RI in the tech industry.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".