Qualitative Analysis of Self- Directed Learning in Nursing Training
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Alireza Jafari , Mohammad Ali Nadi |
, mnadi@khuisf.ac.ir |
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Abstract: (1289 Views) |
Introductiiion: qualitative analysis of self-directed learning components can help to better and more effective learning. The purpose of this study was to identify self-directed learning components in nursing students.
Methods: Attride-Stirling (2001) qualitative method of thematic analysis was used for Identification of self-directed learning components where basic themes identified inductively (based on data) and from basic themes towards learner theme (part-to-whole). Basic themes were identified and extracted by researcher after complete review on all resources in research environment, according to Attride-Stirling (2001) thematic analysis steps .Also the Holstein method was utilized to determine themes coefficient reliability, confirming the opinion of the experts that was estimated to be ./827.
Findings: By reviewing the research literature and opinion polls by experts, 62 themes were identified, and then these factors were classified into ten main dimensions. The ten organizing themes of self-directed learning are as follows: Self-management with 7basic themes, self-monitoring with 4 basic themes, self-learning with 7 basic themes, background or contextual with 8 basic themes, motivation and willingness with 9 basic themes, cognitive and metacognitive strategies with 6 basic themes, individual characteristics with 7 basic themes, learner autonomy with 7 basic themes, interpersonal communication skills with 3 basic themes,and emotional skills with 4 basic themes.
Conclusion: The basic themes of self-directed learning in higher education presented in the current study can be used as a model for teaching and learning programs in the higher education system for nursing students and learners. |
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Keywords: self-directed learning, nursing students, higher education |
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Full-Text [PDF 953 kb]
(716 Downloads)
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Type of Study: Qualitative-Research |
Subject:
Special Received: 2022/01/18 | Accepted: 2022/04/30 | Published: 2022/04/30
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