Cross-sectional online survey of nursing graduates’ academic difficulties and related factors
Bibliographic record
Abstract
Objective: The aim was to explore the ratio of and differences in academic difficulties experienced by nursing graduates with associate or diploma degrees and baccalaureate degrees and the factors related to these difficulties.Methods: A quantitative cross-sectional online survey was conducted with graduate students in the master’s program in nursing from 144 graduate schools throughout Japan. Data were collected from November 2014 to December 2014. Of 1,366 potential respondents, 304 completed the survey (22.3%) and the data of 268 respondents who met the criterion were included in analysis. Experience of academic difficulties was regressed onto characteristics of respondents, such as nursing degree, Self-Directed Learning Readiness (SDLR) score, and having experience in academic activities.Results: Of the respondents, 227 (84.7%) reported they have always or frequently experienced academic difficulties. However, there was no difference in the extent of academic difficulties experienced by respondents with the different nursing degrees. Not having experience in academic activities (odds ratio [OR] = 2.05; 95% confidence interval [CI], 1.02-4.25) and reporting SDLR score less than 150 points (OR = 2.40; 95% CI, 1.18-4.83) were significantly associated with academic difficulties in the graduate school.Conclusions: Most respondents experienced academic difficulties. To promote effective education in the graduate school, pre-educational programs conducted by universities where students can gain experience in academic activities may be effective in reducing academic difficulties experienced by them. Simultaneously, examining how to inculcate an autonomous learning attitude is necessary for both nursing graduate students and graduate schools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".