Computer-based nursing education: An integrative review of empirical studies
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
The goal of this study is to explore the ways in which Computer-Based Nursing Learning (CBNL) has been studied and the findings that have been made with regard to its use in undergraduate nursing education. We undertook an integrative review by selecting papers published in English between 2007 and 2010. We included in the review empirical studies comparing CBNL with other training strategies for clinical skills education in the context of undergraduate nursing education. We carried out an electronic search in which specific keywords were used, and a total of 467 citations were found. Nine of these studies met the inclusion criteria. A list of criteria for evaluating the quality of the empirical studies identified was also used. With regard to the impact of CBNL on skill performance and cognitive recall, the results were positive since most studies reported higher skill and knowledge scores using CBNL. Only two studies tested skill or cognitive retention. Seven studies reported high levels of students' satisfaction with CBNL. However, the authors identified some problems related to technical issues in four studies. Finally, we described and criticized the experiences, since important weaknesses in the experimental designs were detected. We also provided some recommendations for better practices in the research methods.
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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 | 0.004 | 0.005 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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