INTEGRATED LEARNING IN ENGINEERING - DEVELOPMENT OF THE FIRST YEAR ENGINEERING CURRICULUM AT UNB
Bibliographic record
Abstract
Following its rich tradition of over 150 years of excellence in engineering education, the Faculty of Engineering at the University of New Brunswick (UNB) is currently implementing an exciting first year program. In consultation with Atlantic businesses, governments and members of the Faculty, an Engineering Education Task Force was formed in the summer of 2003 with the mandate to enhance integrated learning in undergraduate engineering programs at UNB. The Task Force proposed a substantially-common first year program for all engineering disciplines with design projects in both the first and second terms. The design projects are used to integrate knowledge gained in the first year and are part of two new design courses. The first design course is centered on Design and Communications. The second design course is centered on Design and Computations. This new approach requires that teaching of core materials be integrated at a level that crosses disciplinary boundaries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".