The feasibility of an electronic reflective practice exercise among physiotherapy students
Bibliographic record
Abstract
BACKGROUND: Reflective practice is a skill that serves as a model for continuous learning. Like any skill, reflective practice can be improved and health professional curricula should include opportunities to develop these skills. The clinical component of health professional curriculum is a natural component where reflective practice skills can be developed. Electronic means will help students and faculty stay in contact during clinical internships. AIMS: The purpose of this study was to evaluate the feasibility of an electronic reflective practice exercise during a clinical internship and explore the potential trends on students' reflective practice skills and self-directed learning readiness. METHODS: We used a prospective pre-post intervention design in a cohort of physiotherapy students to examine feasibility and explore trends. Faculty also rated the depth of reflection papers. In addition, students completed a reflective practice exercise questionnaire and the self-directed learning readiness scale (SDLRS) was completed pre- and post-internship. RESULTS: All 84 students completed the reflective practice questionnaire. Sixty-six students consented to complete the questionnaire and 17 consented to complete the SDLRS pre- and post-internship. It took an average of 7 min for faculty to review each student's reflection and there were no significant electronic difficulties encountered. Initial reflection papers were rated at a descriptive (23%), descriptive-analytical (28%) or analytical level (33%). Eighty-six percent of students rated faculty feedback as helpful and 92% rated peer feedback as helpful. Almost all students (97%) students reported that they followed through on some or all of the items on their reflective practice learning plans. The SDLRS significantly improved with the exercise (mean difference 6.8 +/- 9.9; p < 0.05). CONCLUSIONS: This electronic reflective practice exercise during the physiotherapy students' clinical internship was feasible and demonstrated trends to positively impact the learners' skills and self-directed learning readiness.
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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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".