Core Curricula for Postdoctoral Dental Students: Recent Problems, Potential Solutions, and a Model for the Future
Bibliographic record
Abstract
Development of common core curricula for the graduate advanced education/specialty programs in dental schools presents significant challenges. Similarities in graduate education accreditation standards justify such an approach, yet a core curriculum is difficult to achieve for a variety of reasons including scheduling constraints and the capacity of a common, single pathway curriculum to address the specific educational needs of postgraduate students in different disciplines. Additionally, many dental schools are experiencing severe shortages of qualified faculty to provide graduate program instruction. There are no previous reports regarding graduate core curricula and the definition/delivery of such core curricula in advanced education programs in dentistry although there are several reports in the medical literature that support the educational value of a unified core curriculum implemented in a modular format. Graduate curricula are typically designed to provide residents with advanced education/training beyond what is acquired during their predoctoral dental school experience. Advanced education programs must emphasize knowledge and skills that are discipline-specific; however, there is a large amount of common foundational material within the early phases of these programs. Dental schools have attempted to identify and present this common material within the context of an organized shared set of courses/seminars where residents from each advanced education program are scheduled simultaneously. However, there have been problems with the implementation of a shared core curricula including the following: 1) dissimilar educational backgrounds/abilities among residents; 2) relevance of material to all residents; 3) lack of central management; 4) scheduling conflicts; and 5) lack of adequate and consistent program evaluation. In an attempt to resolve these problems, a new comprehensive graduate core curriculum was implemented at the Marquette University School of Dentistry in 2000. This core curriculum was designed to 1) be user-friendly; 2) allow flexibility; 3) meet specific programmatic/accreditation needs for each advanced education program; and 4) provide assessment tools for continuous resident feedback and curriculum improvement. Assessment data obtained from residents, faculty, and program directors indicate that this approach has been successful and has transformed graduate education at Marquette. Thus, this model may prove useful for other institutions seeking to refine or develop graduate core curricula.
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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 | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".