Development and Effect of a SnowBall Teaching-Learning Model based on Flipped Learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In order to nurture nursing talents with good interest in learning as well as adaptability to the field, it is necessary to have conditions for self-directed learning, this study aimed to the creation of an educational environment and teaching-learning methods; thus, developing a model suitable for nursing students is essential. A snowball teaching-learning model based on flipped learning was developed and applied to nursing students' basic nursing practice classes in order to understand the effect on self-directed learning ability, interpersonal ability, and personality. For the study period, from September 1, 2015 to July 31, 2016, 21 second-year students in the Department of Nursing at University D, located in B city, Busan were recruited through convenience sampling. The collected data were analyzed using SPSS WIN (Ver. 21.0). The results of the study indicated there was a significant difference in the self-directed learning ability score from 3.16±0.28 points before the teaching-learning model application to 3.99±0.49 points after the application of the teaching-learning model. There was a significant difference in from 3.67±0.49 points before application to 3.90±0.43 points after application. There was also a significant difference in the personality score, from 3.69±0.49 points before application of the teaching-learning model to 4.06±0.46 points after application. Therefore, since the flipped learning-based snowball teaching-learning model is helpful in improving job competency, repeated experimental studies are suggested to verify the effectiveness.
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| 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 it