Facilitation of Disorientating Events for the RPN to BScN Learner
Bibliographic record
Abstract
Jack Mezirow’s transformative learning theory provides a framework in which to explore learning experiences that facilitate the registered practical nurses (RPNs) who return to school to upgrade their credentials to that of a registered nurse (RN). It is through self-exploration and critically reflection upon previous nursing knowledge that RPNs can begin to enhance their knowledge and transform their practice. Mezirow claims there are precursor steps that adult learners contemplate as they engage in the process of perspective transformation which is initiated by disorientating dilemmas. RPNs who return to school to upgrade their credentials to that of an RN need to critically reflect upon existing nursing knowledge to begin considering new ways of knowing as they transition to an RN. This article presents results from a mixed-methods study that examined the learning experiences of students in one RPN to Bachelor of Science in Nursing (BScN) program in Ontario. Through utilizing King’s learning activity survey and interviews, learning experiences that stimulated disorientating thoughts were identified. Seventy-seven RPN students completed the LAS and 31 students also took part in interviews. Specific learning activities that showed a higher chance of experiencing disorientating dilemmas were self and peer evaluation, written reflections, and scholarly writing. Faculty relationships also significantly influenced students’ comfort in exploring alternative ways of thinking. Courses that stimulated disorientating dilemmas were social determinants of health, and small group nursing courses that used case studies, and substantial collegial dialogue with RPN peers. Nursing faculty need to consider teaching learning modalities that stimulate disorientating dilemma to facilitate transformation in the RPN to BScN learner.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".