A deep learning approach to student registered nurse anesthetist (SRNA) education.
Journal Article (Journal Article)
This manuscript describes the application of deep learning to physiology education of Student Registered Nurse Anesthetists (SRNA) and the benefits thereof. A strong foundation in physiology and the ability to apply this knowledge to challenging clinical situations is crucial to the successful SRNA. Deep learning, a well-studied pedagogical technique, facilitates development and long-term retention of a mental knowledge framework that can be applied to complex problems. Deep learning requires the educator to facilitate the development of critical thinking and students to actively learn and take responsibility for gaining knowledge and skills. We applied the deep learning approach, including flipped classroom and problem-based learning, and surveyed SRNA students (n=127) about their learning experience. Survey responses showed that the majority of students favored the deep learning approach and thought it advanced their critical thinking skills. SRNAs reported that their physiology knowledge base and critical thinking benefited from the use of the deep learning strategy.
Full Text
Duke Authors
Cited Authors
- Walker, JKL; Richard-Eaglin, A; Hegde, A; Muckler, VC
Published Date
- June 2021
Published In
Volume / Issue
- 18 / 1
PubMed ID
- 34166591
Electronic International Standard Serial Number (EISSN)
- 1548-923X
International Standard Serial Number (ISSN)
- 2194-5772
Digital Object Identifier (DOI)
- 10.1515/ijnes-2020-0068
Language
- eng