Assessment of nursing students in clinical practice - An intervention study of a modified process
Bibliographic record
Abstract
Objective: To evaluate an intervention of a modified assessment process for nursing students in clinical practice and how this process was experienced by the nursing students and their supervisors.Methods: An intervention study with a descriptive approach. The data collection was conducted in two phases with a survey and follow-up group interviews. Participants were second-year nursing students and their nursing supervisors. Descriptive statistics were used for the quantitative data (survey) and qualitative content analysis for the qualitative data (tape-record and transcribed interviews). Mixed method was used to integrate all data.Findings: The survey response rate was 65% (n = 41 students) and 100% (n = 9 supervisors). Students and supervisors found the assessment tool applicable for the assessment process. Assessment through dialogue and Supportive learning environment, describe how the modified assessment process was experienced.Conclusions and implication for clinical practice: It is important that the supervisors understand the learning goals and assessment criteria and how to use the assessment tool. Clear structures based on learning goals and assessment criteria as well as their own strategies to reach their goals benefit student learning. Strategies need to be developed to facilitate the assessment process when the teachers from the university have a consulative role. The new assessment tool and changing the university teachers’ involvement can be seen as a form of professional development of the supervisors’ group as they take greater responsibility in conducting the assessment of nursing students in clinical practice.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".