The Intention to Pursue Graduate Studies in Nursing: A Look at BScN Students' Self-Efficacy and Value Influences
Bibliographic record
Abstract
The shortage of graduate-level prepared nurses is reaching critical levels. Combined with an anticipated wave of faculty retirements, a relatively older graduate student body, and an insufficient number of graduates at the Masters' and doctoral levels, the recruitment of more and younger students into graduate programs in nursing has become a priority for the profession. Current understanding of why undergraduate nursing students choose to pursue graduate studies in nursing remains vague. A non-experimental descriptive correlational study was designed and 87 useable surveys were collected from fourth-year baccalaureate nursing students at a large South-Western Ontario University (response rate = 67%). The influence of student valuation of graduate studies and self-efficacy (SE) for graduate studies on student intention to pursue graduate studies in nursing was clearly demonstrated with this study (R(2) = .52). Implications for nursing education include working towards undergraduate curricula that enhance students' valuation of and SE for graduate studies in nursing.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".