Students’ Reflective Learning Within a Community Service‐Learning Dental Module
Bibliographic record
Abstract
This article aims to illustrate the effect of reflections upon students' learning in a newly developed dental module at the University of British Columbia. Students reflected individually before, during, and after the development of their community service-learning (CSL) projects. One hundred twenty-one students provided reflections through e-mail, a password-protected intranet site (WebCT), or handwriting. Reflections were not graded, and students were encouraged to favor thinking over description in a total of at least 150 words. Eighty-two students were from two first-year classes, and thirty-nine were from one second-year class. Reflections were analyzed thematically using framework analysis. Students appreciated the community experience and also pondered their own learning as health care providers. Reflections before the CSL projects emphasized "expectations" and "feelings of belonging," whereas reflections during and after the projects promoted discussions on "challenges and struggles" and "ongoing engagement," respectively. A circular and bidirectional illustration portrays students' activities in reflecting, rethinking, reconsidering, reanalyzing, reconstructing, and reacting on their CSL experience. Reflective activity helped students to better appreciate the CSL experience within a newly developed dental course. It allowed them to gain additional value from community-based education and had a positive impact on their attitudes about service, themselves, and the community members enrolled within their projects.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".