Bibliographic record
Abstract
This thesis investigated the role of knowledge building pedagogy and technology in medical education. The literature in medical education points to a need for change to better address society's needs for greater community orientation in medicine and integration of new knowledge media. These goals are reflected in the Canadian Medical Education Framework of the Royal College of Physicians and Surgeons. Knowledge Building is an innovative theoretical framework and pedagogy with emphasis on the engagement of all community members in contributing ideas of value to local communities and society, facilitated by Internet-based knowledge building environments. The goal of this research was to determine the applicability and usefulness of knowledge building across various levels in medical education. Case studies were conducted in four University of Toronto contexts: undergraduate Foundations of Medical Practice Course, Obstetrics/Gynecology Graduate Residency Program, Graduate Family Medicine Residency Program, and Psychiatry Continuing Medical Education Course. An online knowledge building environment, Knowledge Forum, supported the knowledge building work which was conducted over a series of investigations lasting 1 to 16 weeks, with the investigations largely conducted as add-ons to course work. Fifty-seven participants (teachers and students) were engaged in these four contexts; 75% volunteered for the add-on component. Thirty-six months after the pilot investigations the four professors were interviewed to assess current practices and beliefs. Analyses focus on barriers and challenges in integrating knowledge building principles and technologies into medical education. Discourse analysis revealed expert-dominated discourse---in many ways right-answer-driven and exam-based, and leaving little room for student contributions, constructive engagement with authoritative sources, or self- and group-assessment. Teacher-generated activities, along with a curriculum with large amounts of prescribed information to be learned, made it difficult for students to find time to work creatively with ideas, consult additional sources, or reflect on diagnoses and prescriptions. The belief that knowledge innovation should occur after the acquisition of foundational knowledge, not in parallel, reflected a tension between espoused ideals and "add-on" status for knowledge building pedagogics and technologies. Results are consistent with the literature on change, suggesting that reform will be slow, but propelled by prevailing expectations of change and new knowledge media.
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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".