Blended learning in a health assessment course: A mixed-methods study
Bibliographic record
Abstract
Objective: The purpose of this study was to get students’ perceptions about changes made to the health assessment course delivery format from face to face to blended learning (BL). Health assessment is a foundational course in nursing undergraduate programs. Research has suggested that students have high levels of satisfaction with a blended learning format.Methods: A survey was used to gather students’ perceptions about changing a health assessment course from face-to-face delivery format to a blended learning format. All second year BSN students who were registered for the course (N = 88) were invited to participate in the survey at the end of the semester.Results: Most students in this study preferred face to face course delivery. Qualitative results were grouped together into themes: 1) Engagement, 2) E-learning tool, and 3) Confidence. Opinions were mixed concerning the e-learning materials that were used. Overall, students felt they were confident in their assessment skills as they prepared to enter the clinical environment.Conclusions: Findings from this study will impact methods of teaching health assessment and other nursing courses in the future.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".