Developing a Sustainable Electronic Portfolio (ePortfolio) Program That Fosters Reflective Practice and Incorporates CanMEDS Competencies Into the Undergraduate Medical Curriculum
Bibliographic record
Abstract
The University of Ottawa (uOttawa) Faculty of Medicine in 2008 launched a revised undergraduate medical education (UGME) curriculum that was based on the seven CanMEDS roles (medical expert, communicator, collaborator, health advocate, manager, scholar, and professional) and added an eighth role of person to incorporate the dimension of mindfulness and personal well-being. In this article, the authors describe the development of an electronic Portfolio (ePortfolio) program that enables uOttawa medical students to document their activities and to demonstrate their development of competence in each of the eight roles. The ePortfolio program supports reflective practice, an important component of professional competence, and provides a means for addressing the "hidden curriculum." It is bilingual, mandatory, and spans the four years of UGME. It includes both an online component for students to document their personal development and for student-coach dialogue, as well as twice-yearly, small-group meetings in which students engage in reflective discussions and learn to give and receive feedback.The authors reflect on the challenges they faced in the development and implementation of the ePortfolio program and share the lessons they have learned along the way to a successful and sustainable program. These lessons include switching from a complex information technology system to a user-friendly, Web-based blog platform; rethinking orientation sessions to ensure that faculty and students understand the value of the ePortfolio program; soliciting student input to improve the program and increase student buy-in; and providing faculty development opportunities and recognition.
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.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".