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 24, 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