Graduate nursing students’ writing proficiency: Survey of faculty perspectives and academic active inertia
Bibliographic record
Abstract
Background and objectives: In the last two decades, enrollment in doctoral programs in nursing has increased dramatically. Completion of these advanced degrees is being hampered by prevailing weaknesses in a key competency that is critical to graduate nurses’ ability to successfully complete their graduate program: academic writing proficiency. These weaknesses endanger the success of graduate nursing programs and the nursing profession’s ability to meet its primary professional obligation: advancement of scientific knowledge through professional publications, policy briefs, business cases, and innovative, evidence-based projects. This research aimed to determine the national nursing faculty’s perceptions of graduate nurses’ writing skills and techniques used to improve their writing proficiency.Methods: The authors employed a descriptive online survey design to examine perspectives on the state of writing proficiency in graduate nursing programs in a nationwide sample of 2,234 faculty members. Statistical analyses included the calculation of percentages for all categorical variables and means, standard deviations, and ranges for continuous variables.Results: The survey results describe a myriad of pervasive weaknesses in graduate nurses’ writing and the limited effectiveness of techniques used to improve writing skills.Conclusions: The article concludes with an association between writing problems in nursing and the concept of active inertia in academia and suggestions for advancing this growing concern to the top of nursing’s agenda and training nursing faculty.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".