Against the Current: Lived Experiences of Nursing Educators with Concept-Based Curriculum in Canada
Bibliographic record
Abstract
Reforming nursing education from a content-heavy, traditional teaching style to a concept-based one has become necessary to meet the constant change in the health care system. However, in general, no studies have been conducted on the lived experiences of faculty members and educators in Canada after years of implementing the concept-based curriculum (CBC). This qualitative phenomenological study aimed to uncover the meaning of the lived experiences of the faculty members and educators after seven years of reforming the nursing curriculum to a concept-based one. Giorgi's phenomenological descriptive method was used to collect data using semi-structured interviews with three doctoral-prepared faculty members and two master-prepared educators who teach in the undergraduate nursing program at Cape Breton University, Canada. The recorded data was transcribed verbatim and analyzed and synthesized using Giorgi's five data analysis steps. The findings of this study revealed that the nursing educators indicated they had challenging experiences teaching CBC. The major General Structural Descriptions (GSD) that emerged were Rowing Against the Current and Save Us Before We All Drown. The findings were discussed and conceptualized within the relevant literature. This study highlights the challenges nursing educators face when implementing a CBC, including resistance from students and colleagues, increased workload, and concerns about graduate quality. Therefore, a gradual introduction of CBC is recommended, which will help ease the transition for students and educators. Building supportive substructures is also crucial to handle the increased demands and pressures.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".