Comparative study of nursing curriculum in nursing faculties of Canada, Turkey, and Iran according to SPICES model
Bibliographic record
Abstract
BACKGROUND: Innovation in the development and review of curriculums is one of the requirements of medical education in the present era. SPICES model has been taken into consideration by nursing faculties to promote quality of nursing education and to eliminate conventional curriculums. In Iran, for competency-based nursing education, review and development of curriculums are necessary. OBJECTIVE: The objectives of the present study were to determine the implementation of SPICES model in nursing curriculums of Tehran (Iran), Western (Canada), and Hacettepe (Turkey) nursing faculties and also to present recommendations to operationalize it in the nursing curriculum of Iran. MATERIALS AND METHODS: This study using comparative method with Brady's model was conducted in 2018. In this study, curriculums of nursing faculties of Tehran, Western Canada, and Hacettepe were compared. Data were extracted through texts and documents available at electronic pages of universities. Curriculums of these nursing faculties were compared from the perspective of SPICES model strategies (student-based, problem-based, integration, community-based, elective, and systematic) at four steps of description, interpretation, juxtaposition, and comparison. RESULTS: The results showed that curriculums in Western Canada reside at the end of the innovative spectrum of SPICES model. Curriculums in Tehran and Hacettepe in most of the strategies of this model reside at the beginning of the spectrum, and in most cases, conventional methods were used. CONCLUSIONS: According to successful experiences of Western Canada in the implementation of SPICES model's strategies and also considering this fact that still conventional approaches are prevalent in Iran, it is recommended to focus on experiences and, according to social conditions and facilities of the nursing community, to implement necessary changes in the curriculums based on this model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".