Biomedical engineering undergraduate education: A Canadian perspective
Bibliographic record
Abstract
Background With an aging population and increasing demand on health care systems, biomedical engineering as an undergraduate program fits a growing societal need. As such, many Canadian universities have implemented biomedical engineering undergraduate programs. This provides a unique opportunity for core engineering faculty, engineering education researchers, and curriculum specialists to implement proven educational theories in the core curriculum of these programs to ensure exemplary and competent Canadian-trained biomedical engineering graduates. Purpose This paper discusses the need for biomedical engineering as a core undergraduate program in Canada, the historical context of educational theories as related to biomedical undergraduate engineering education, a framework for the implementation of proven strategies, and learner-centric methods that benefit the learner, mentor, and society as a whole. Scope/method: The historical context of curriculum theories related to biomedical engineering undergraduate education, evaluation of the intrinsic and extrinsic curriculum theories in current biomedical engineering undergraduate education, educating progressive learners and development of future biomedical engineering undergraduate education curriculum, is explored. Conclusion The integration of educational theories in the development of a biomedical engineering undergraduate engineering education is essential to ensure learners are provided with opportunities to experience cutting edge, quality engineering education. Empirical evidence demonstrates the successful implementation of applied methodologies such as model-electing activities, problem-based learning, and the flipped classroom. Providing biomedical engineering faculty with professional development opportunities around the successfully implementation of these tools aimed at culturally diverse, globalized 21st-century learners, can be catalytic in shifting to a new paradigm for engineering education in Canada and globally.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".