Student support services: Perceptions and recommendations for the next generation
Bibliographic record
Abstract
PURPOSE: Student support services/student affairs are central to the student academic experience and success at US and Canadian dental schools. This manuscript evaluates student and administrator perceptions of support services and offers recommendations for best practices in student services in predoctoral dental education to help institutions improve the student experience. METHODS: A survey of administrators and dental students found perceptions of student support services vary between these groups. RESULTS: Seventeen student services administrators and 263 students started the survey, and 12 administrators and 156 students completed the full survey. Survey comments indicated access to student support services is a concern. Results of the student survey, in conjunction with current literature, were utilized to develop recommendations for dental student support services. CONCLUSION: Recommendations for student support services in dental schools include accessibility of student services, and ensuring students have access to support in the domains of wellness, academic support, and peer support as well as implementation of humanistic practices. Wellness supports should include behavioral health services, physical health services, and access to mindfulness interventions. Academic support services should include study skills, time management training, and academic supports such as tutoring. Structured peer support programs should also be implemented. Dental schools should also be mindful of the changing support needs of incoming dental students.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".