NURSING STUDENTS’ LEARNING EXPERIENCES IN AN ONLINE LEARNING COURSE
Notice bibliographique
Résumé
<p>To improve the quality of online learning in Indonesia higher education, Faculty of Nursing (FoN), Universitas Pelita Harapan (UPH) supported by the Directorate of Higher Education in Indonesia that known as DIKTI developed an online course named Family Nursing. The course is a community nursing course in regard with the care of family nursing and it discusses the concept of family, family health, and the concept of a wellness family. The course was developed to achieve the mission of equitable access to information, relevance, and improvement of the quality of higher education throughout Indonesia, especially in nursing education. The online course was offered in one private nursing school in Jakarta area that never had any online course nor using online learning method in the delivery of their subjects. The aim of this report was to describe students’ experiences in an online course. This paper reports on the evaluation work of one semester online/blended learning project funded by DIKTI. Sixty five students, who experienced the online/blended learning method for the first time, were enrolled in the online course. The students have agreed to fill an evaluation online form after their mid semester exam. The evaluation form consisted of closed- and openended questions. This report revealed that most students (&gt; 70%) agreed that their experience on the online (blended) learning was positive. However, it should be noted that, a quarter of students (27-28%) had less motivation to do the independent learning and perceived that the online learning was a learning experience that lack of support in developing their critical thinking. Several important themes further emerged including students’ issues (lack of knowledge and motivation), teaching-learning process issues (lack of facilities and clarity) and academic staff issues (minimal feedback and different perceptions between academic staff and students). Though online/blended learning can be employed to support nursing and healthcare education, there is limited appreciation of students' experience and the use of e-learning. Context is also being considered as an important part when applying the online/blended learning, thus, this report provides a new understanding of students’ opinions on their first experience when engaging with online learning at a private nursing school. This report further provides a number of inhibiting factors continue to affect the student experience.</p>
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».