Discourse / Discours - Status of Informatics Integration in Baccalaureate Nursing Education: A Systematic Review
Bibliographic record
Abstract
The purpose of this study was to map out results of research studies and other projects on the integration of informatics into BScN education and to highlight implications of this work for education and research. The systematic review of the literature from 1990 to 2011 excluded articles reporting on non-BScN students or nurses already in practice. A total of 440 articles were found, 53 of which were eligible for inclusion in this review; 21 articles were added based on reference lists of key works. Integration of informatics into BScN education was found to vary in terms of focus, duration, and strategies used. The main issues identified were inconsistent integration of informatics content and lack of rigorous research studies on the process and outcomes of informatics education. More work is needed to specify the core informatics content needed in BScN education, followed by a systematic evaluation of the effect of this education.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".