A Study of factors affecting clinical performance grades of nursing students
Notice bibliographique
Résumé
This study involved an investigation of factors affecting clinical performance grades of first and second year nursing students in a two-year Diploma program. The purpose of the study was to increase knowledge of factors which may correlate with clinical performance of nursing students; related goals were to assist nurse educators in predicting student clinical performance and providing guidance accordingly. The study was planned to test the following hypotheses: 1 . Grades in Nursing, Biology, and Psychology courses during the first semester of the nursing program account for a significant proportion of the variance in clinical performance scores of students; 2. Complexity of the nursing situation accounts for an additional significant proportion of the variance in clinical performance scores of students. The study population consisted of 59 first and second year nursing students. The dependent variable was the average of the clinical performance scores of the students given by the clinical instructors (who wrote and scored the anecdotal records) and two nursing judges (who scored the written anecdotal records). The independent variables were the grades in first semester Nursing, Biology, and Psychology; and the complexity of the nursing situation. Data for the study were collected over a three-week period. This phase included: (a) writing of anecdotal records of students' clinical performance by their instructors, and subsequently scoring of these records by the clinical instructor and two nursing judges using the scoring instrument; (b) assessing the level of complexity of the students' clinical assignments by their clinical instructors, using the complexity of the nursing situation instrument; and (c) obtaining the students' first semester Nursing theory, Psychology, and Biology grades from their permanent records. The clinical instructors and the nursing judges were trained in the writing and scoring of anecdotal records, and in determining the complexity of the students' assignments by utilizing a 10 minute videotape prepared by the investigator depicting the performance of a nursing student in a simulated clinical situation. Analyses of the data were carried out in two phases. Phase one included product moment correlational analysis and general izabi I ity analysis to determine the reliability of the clinical scores. Phase two included stepwise multiple regression analysis to determine the predictors of clinical scores. The findings of the study showed that the inter-rater correlations among the clinical instructors and two nursing judges were moderately strong (.58 to .84). Likewise generalizability analysis showed that the clinical scores were reliable. The data on complexity of the nursing situation showed very little variability in each of the four semesters and were therefore deleted from the regression analysis. The regression analysis showed that in Semesters II and III 51 and 76 percent of the variance in clinical performance scores could be accounted for by the grades in first semester Nursing, Psychology, and Biology. However, in Semesters IV and V the amount of variance accounted for by the independent variables was not significant. Thus, hypothesis 1 is accepted in the case of Semester II and III students, and rejected in the case of Semester IV and V students.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».