Exploring deep learning in third-year undergraduate nursing students: a mixed methods study

Abstract Background Deep learning is an important way for nursing undergraduates to develop professional skills. It is helpful for these students to successfully complete clinical practice and provide high-quality care. However, research focusing on deep learning in nursing undergraduates is scarce....

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Main Authors: Wenjuan Wang, Dan Song, Panpan Zhang, Wan Mi, Wenli Xu, Lihua Zhou
Format: Article
Language:English
Published: BMC 2025-06-01
Series:BMC Nursing
Subjects:
Online Access:https://doi.org/10.1186/s12912-025-03303-6
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author Wenjuan Wang
Dan Song
Panpan Zhang
Wan Mi
Wenli Xu
Lihua Zhou
author_facet Wenjuan Wang
Dan Song
Panpan Zhang
Wan Mi
Wenli Xu
Lihua Zhou
author_sort Wenjuan Wang
collection DOAJ
description Abstract Background Deep learning is an important way for nursing undergraduates to develop professional skills. It is helpful for these students to successfully complete clinical practice and provide high-quality care. However, research focusing on deep learning in nursing undergraduates is scarce. Aims To develop an intervention program for deep learning using unfolding case-based learning (CBL) based on the CoI framework and to evaluate the effects of this intervention program among nursing undergraduates. Methods A sequential explanatory mixed methods design was used. The quantitative study was followed by a qualitative study, the results of which were used to better explain and understand the results of the quantitative study. From September 2023 to January 2024, 132 students participated in the study. The quantitative component consisted of pretest-posttest of students’ deep learning and academic assessment scores. The qualitative component consisted of semistructured interviews with 12 students. Results The quantitative results revealed that students’ deep learning significantly improved during unfolding case-based learning (P < 0.05), the scores for which were greater than were those for students with traditional learning (P < 0.05). Students who applied blended teaching exhibited no significant change in deep learning (P > 0.05). The qualitative data analysis identified three themes: (1) gain and experience, (2) difficulties and challenges, and (3) individual career development. Conclusion Incorporating case-based training into a course helps enhance deep learning for students. In the future, consideration may be given to continuing targeted reforms in the integration of learning methods to help students enhance their career confidence and prepare to become professional nurses. Clinical trial number Not applicable.
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spelling doaj-art-e6c2c5a5d9db4f52b6fafd65bdc9aad62025-08-20T02:31:03ZengBMCBMC Nursing1472-69552025-06-012411910.1186/s12912-025-03303-6Exploring deep learning in third-year undergraduate nursing students: a mixed methods studyWenjuan Wang0Dan Song1Panpan Zhang2Wan Mi3Wenli Xu4Lihua Zhou5School of Nursing, Anhui Medical UniversitySchool of Nursing, Anhui Medical UniversitySchool of Nursing, Anhui Medical UniversitySchool of Nursing, Anhui Medical UniversitySchool of Nursing, Anhui Medical UniversitySchool of Nursing, Anhui Medical UniversityAbstract Background Deep learning is an important way for nursing undergraduates to develop professional skills. It is helpful for these students to successfully complete clinical practice and provide high-quality care. However, research focusing on deep learning in nursing undergraduates is scarce. Aims To develop an intervention program for deep learning using unfolding case-based learning (CBL) based on the CoI framework and to evaluate the effects of this intervention program among nursing undergraduates. Methods A sequential explanatory mixed methods design was used. The quantitative study was followed by a qualitative study, the results of which were used to better explain and understand the results of the quantitative study. From September 2023 to January 2024, 132 students participated in the study. The quantitative component consisted of pretest-posttest of students’ deep learning and academic assessment scores. The qualitative component consisted of semistructured interviews with 12 students. Results The quantitative results revealed that students’ deep learning significantly improved during unfolding case-based learning (P < 0.05), the scores for which were greater than were those for students with traditional learning (P < 0.05). Students who applied blended teaching exhibited no significant change in deep learning (P > 0.05). The qualitative data analysis identified three themes: (1) gain and experience, (2) difficulties and challenges, and (3) individual career development. Conclusion Incorporating case-based training into a course helps enhance deep learning for students. In the future, consideration may be given to continuing targeted reforms in the integration of learning methods to help students enhance their career confidence and prepare to become professional nurses. Clinical trial number Not applicable.https://doi.org/10.1186/s12912-025-03303-6Deep learningCase-based learningNursing students
spellingShingle Wenjuan Wang
Dan Song
Panpan Zhang
Wan Mi
Wenli Xu
Lihua Zhou
Exploring deep learning in third-year undergraduate nursing students: a mixed methods study
BMC Nursing
Deep learning
Case-based learning
Nursing students
title Exploring deep learning in third-year undergraduate nursing students: a mixed methods study
title_full Exploring deep learning in third-year undergraduate nursing students: a mixed methods study
title_fullStr Exploring deep learning in third-year undergraduate nursing students: a mixed methods study
title_full_unstemmed Exploring deep learning in third-year undergraduate nursing students: a mixed methods study
title_short Exploring deep learning in third-year undergraduate nursing students: a mixed methods study
title_sort exploring deep learning in third year undergraduate nursing students a mixed methods study
topic Deep learning
Case-based learning
Nursing students
url https://doi.org/10.1186/s12912-025-03303-6
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