Effectiveness of a training program based on maker education for baccalaureate nursing students: A quasi-experimental study
Bibliographic record
Abstract
OBJECTIVES: Maker education is a dominant force in education reform and is viewed as a revolutionary way to learn. As innovative pedagogy is continuously explored in the field of nursing, the emerging role of maker education must be examined. This research aims to build a nursing bachelor education program based on maker education and to evaluate the effectiveness of this program. METHODS: Forty volunteer junior students majoring in nursing from a college were the subjects for this quasi-experiment. The training program for nursing students based on maker education was developed and implemented as an additional class for a period of 12 weeks. Before and after the experiment, two measures including the "Williams Creative Scale" and "Current Status Questionnaire of Nursing Students' Learning" were adopted for investigation, and corresponding statistical methods were used for analysis. The degree of satisfaction with this training program was investigated after the experiment. RESULTS: < 0.05). Most of the students expressed satisfaction with this training program (72.5% were very satisfied, 15.0% were partially satisfied, and 12.5% were not satisfied). CONCLUSION: Implementing the training program based on maker education enhanced student creativity, learning interest, cooperative learning skill, scientific research ability, and information attainment. Comprehensive nursing talents were also cultivated. Our data suggested the importance of improving this program, adopting the method, and pursuing research in nursing education.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".