Comparing Practice Management Courses in Canadian Dental Schools
Bibliographic record
Abstract
Practice management has become an increasingly important aspect of dental education over the years in order to better prepare students for the reality of practice. The aim of this study was to quantify and describe practice management courses taught at the ten Canadian dental schools in order to identify common approaches, compare hours, determine types of instructors, and assess the relationship between courses' learning objectives and the Association of Canadian Faculties of Dentistry (ACFD) competencies and Bloom's cognitive levels. The academic deans at these ten schools were surveyed in 2016; all ten schools responded for a 100% response rate. The authors also gathered syllabi and descriptions of the courses and analyzed them for themes. The results showed a total of 22 practice management courses in the ten Canadian dental schools. The courses provided 27 to 109 hours of teaching and were mostly taught in the third and fourth years and by dentists on three main topics: ethics, human resource management, and running a private practice. The courses were correlated to the ACFD competencies related to ethics, professionalism, application of basic principles of business practices, and effective interpersonal communication. Most of the courses' learning objectives addressed comprehension and knowledge in Bloom's cognitive levels of learning. These results can help to guide discussions on how practice management courses can be developed, improved, and refined to meet the challenges of preparing students for dental practice.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".