Implementation of a flipped classroom: Nursing students’ perspectives
Bibliographic record
Abstract
The need to update nursing curriculum has prompted the development of new pedagogies designed to engage students and help them develop clinical reasoning skills. This descriptive phenomenological study explored student experiences of “flipping the classroom” in two Medical/Surgical courses. “Flipping the classroom” is in contrast to a traditional class where lecture is given in class and assignments are sent as homework. Instead, with the flipped classroom, lecture is sent as homework and class time is devoted to active learning assignments. By making the lecture available to students outside of the classroom, class time can then be spent on innovative learning activities designed to engage the students in actively learning the lecture material. The flipped classroom can enhance the learning experiences of nursing students in Medical/Surgical courses; however, there are challenges related to this transformative process. The shift from a traditional, passive learning approach to a non-traditional active learning method is discussed through the lived experience of students as recipients of this innovative teaching strategy.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".