Electro-Mechanical Design Engineering: A Progress Report and Future Directions for Mechatronics Education
Bibliographic record
Abstract
The Electro-Mechanical Design Engineering programme has been in place as a five-year combined interdisciplinary programme in mechanical and electronics engineering at the University of British Columbia since 1994. The students take almost all mechanical and most of the core electronics engineering courses during the first four years. They spend at least two four-month-long summer terms in industry as cooperative education students, where they receive training in practical design, drafting, manufacturing and instrumentation. The fifth year is dedicated to the complete design and manufacturing of a computer controlled machine in industry. Teams of students design the complete mechanical system with actuators, sensors and computer control units under the joint supervision of a faculty member and a qualified engineer designated by the sponsoring company. Upon the completion and testing of the full electro-mechanical machine and four graduate courses, the students receive a Bachelor and Master of Engineering in Electro-Mechanical Engineering. The Electro-Mechanical students receive academic and industrial training in mechanical, electronics and software engineering, and are in high demand in industry and academia upon graduation. The present status and future of this programme, including the proposed expansion of the programme to the M.A.Sc. Degree (currently under faculty review), is discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".