ArticleBMC nursing2025
Exploring deep learning in third-year undergraduate nursing students: a mixed methods study.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Academic emotions, self-efficacy, and deep learning behaviors in online nursing education: a mediation analysis.Frontiers in public health · 2026Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundDeep 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.
aimsTo 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.
methodsA 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.
resultsThe 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.
conclusionIncorporating 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.