JOURNAL ARTICLE
The approaches and motivations to learning of student nurses: a phenomenological study.
Published In: British Journal of Nursing, 2023, v. 32, n. 14. P. 684 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Morrell-Scott, Nicola 3 of 3
Abstract
This research study was undertaken to elicit a group of final-year student nurses' perceptions of their motivations and approaches to learning, and the implications of their views. It is important to explore this subject because students' motivations and approaches to learning can potentially impact patient care. This study was part of a larger research project. The sample consisted of 18 final-year student nurses at a large UK university. Students completed semi-structured interviews that used a qualitative constructivist approach to explore their educational experience. Students described what motivated them to learn, and how they approached their learning because of their understanding of which subjects they believed were and were not important. Students felt that clinical skills were the most important subjects, and topics such as health promotion, law and ethics, were less important and therefore they approached these subjects in a superficial way, learning just enough to pass their course. Clinical skills were perceived as more useful because they would be used directly in clinical practice. The findings of this study are significant to inform nurse educators as they plan curricula and provide an insight into what may potentially adversely affect patient care when students become registered nurses. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:British Journal of Nursing. 2023/07, Vol. 32, Issue 14, p684
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2023
- ISSN:0966-0461
- DOI:10.12968/bjon.2023.32.14.684
- Accession Number:167306756
- Copyright Statement:Copyright of British Journal of Nursing is the property of Mark Allen Holdings Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.