A cross-sectional study of pedagogical strategies in nursing education: opportunities and constraints toward using effective pedagogy
Bibliographic record
Abstract
BACKGROUND: The continuous, rapid evolution of medical technology, the public need for ever more complex health-care services and the stagnant global economic situation have posed difficult new challenges for the nursing profession. The need to integrate knowledge, technical skill and ethical conduct in nursing practice has become ever more evident, particularly in response to the emerging challenges over recent years. Major research studies have highlighted that high-quality responses to health needs is highly dependent on both the education received by health care professionals and the pedagogical strategies employed in such training. The aim of this study was to identify the pedagogical strategies used by teachers in nursing programs in the Italian university system and to classify them according to the didactic architectures that are used. METHODS: The study sample was recruited from the entire population of nursing instructors teaching in all years of their respective programs, in every Italian university with a nursing program. A three-part questionnaire, based on a Calvani taxonomy, was designed to collect both demographic and cultural information on the sample subjects, as well as the pedagogical strategies that they may have used in their teaching practices, was administered to all nursing instructors. A five-point Likert scale was used to measure the frequency of use of different pedagogical strategies. RESULTS: On the whole, 992 teachers participated in the study (80.1% of the teachers contacted). Experience data suggest a highly-educated overall instructor population. The settings in which the participants carried out their teaching activities were represented mostly by large lecture halls and the number of students in their classes were for the most part rather large; over 60. Frequency of use revealed that the most commonly used method was the traditional lecture. Indeed, 85.7% of the respondents "often" or "always" used pedagogical strategies belonging to a 'receptive architecture'. CONCLUSIONS: Any redefining of approaches to nursing education must consider several key factors to ensure the promotion of student-focused pedagogical strategies. Only through the implementation of such pedagogical practices will it be possible to generate the knowledge and skills necessary for future professionals to be able to adequately respond to the ever more complex health care needs of the population.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".