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

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.