CAS2E STUDY – FROM STUDENT ENGAGED EDUCATIONAL DESIGN TO LEARNER LED EDUCATIONAL DESIGN
Bibliographic record
Abstract
Engineering education has many gaps between expectations and reality. Students’ mental health and wellbeing is insufficiently considered when designing courses and programs. Current course design is not inclusive of different learning styles. Companies commonly require 3-5 years of experience for entry level jobs because their new hires are not learning enough with their post-secondary education. Graduate schools are noting similar concerns with their incoming students. We argue that today’s engineering students need: a better educational experience; more accommodating and inclusive course and program design; and a smaller gap between their education and the outcomes they need for success beyond their studies. We propose addressing this with four methods: involving student voices in decisions on design; gamification of educational spaces and the student’s educational experience; introducing more inclusive design into programs and courses; and using work-integrated and project-based learning in more fields of study in Higher Education Institutions (HEIs).
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".