Teaching engineering for a changing landscape
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
Abstract Engineering educators face a rapidly changing, and ever more challenging world. Rapidly evolving industry demands, accreditation agencies, and students themselves are calling for an engineering education with integrated multidisciplinary design knowledge, leadership, communication, business, education, entrepreneurship, sustainability, and lifelong learning explicitly included in their undergraduate programs. Students still need the core content knowledge of thermodynamics, mass, energy, and momentum balances and fluxes. They also need integrated socio‐contextual knowledge to evaluate a design for sustainability and demonstrate a net positive social benefit. There is only so much time available in an undergraduate program and learning takes time. These challenges are driving changes to both what and how we teach our students to integrate broader competencies and enhance engineering student graduate attribute achievement. A framework for engineering education includes fundamental and socio‐contextual knowledge integrated with metacognitive and professional skill development. This contribution provides practical ideas for how to infuse these dimensions into courses, support the developing engineering practice, and deepen student engagement with their courses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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