A Model of Cooperative Engineering Didactics for the Training of Identity within the Engineering Activity
Bibliographic record
Abstract
As engineering increasingly intersects with societal challenges, developing interpersonal competencies is essential. This study investigates how a community-based, service-learning course fosters such competencies in senior engineering students. The EPICS-IMPRINT course engaged participants in designing and delivering technology education workshops to secondary school pupils. A qualitative mixed-methods approach guided data collection through classroom observations, interviews, and reflective journals. Results show that students improved their ability to communicate engineering concepts to non-specialists, collaborated effectively with education students, and developed a more reflective understanding of their professional identity. The experience supported growth in adaptive communication, teamwork, and responsibility through authentic engagement. These findings indicate that integrating cooperative outreach projects into engineering curricula strengthens key professional competencies. This pedagogical model aligns technical education with real-world demands and offers a promising avenue for curricular innovation. Future research should investigate its long-term influence on graduates’ trajectories and compare its effects with traditional instructional approaches.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".