Skip to main content
Journal cover image

A deep learning approach to student registered nurse anesthetist (SRNA) education.

Publication ,  Journal Article
Walker, JKL; Richard-Eaglin, A; Hegde, A; Muckler, VC
Published in: International journal of nursing education scholarship
June 2021

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.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

International journal of nursing education scholarship

DOI

EISSN

1548-923X

ISSN

2194-5772

Publication Date

June 2021

Volume

18

Issue

1

Related Subject Headings

  • Thinking
  • Students, Nursing
  • Problem-Based Learning
  • Nursing
  • Nurse Anesthetists
  • Humans
  • Deep Learning
  • 4205 Nursing
  • 4204 Midwifery
  • 1302 Curriculum and Pedagogy
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Walker, J. K. L., Richard-Eaglin, A., Hegde, A., & Muckler, V. C. (2021). A deep learning approach to student registered nurse anesthetist (SRNA) education. International Journal of Nursing Education Scholarship, 18(1). https://doi.org/10.1515/ijnes-2020-0068
Walker, Julia K. L., Angela Richard-Eaglin, Akhil Hegde, and Virginia C. Muckler. “A deep learning approach to student registered nurse anesthetist (SRNA) education.International Journal of Nursing Education Scholarship 18, no. 1 (June 2021). https://doi.org/10.1515/ijnes-2020-0068.
Walker JKL, Richard-Eaglin A, Hegde A, Muckler VC. A deep learning approach to student registered nurse anesthetist (SRNA) education. International journal of nursing education scholarship. 2021 Jun;18(1).
Walker, Julia K. L., et al. “A deep learning approach to student registered nurse anesthetist (SRNA) education.International Journal of Nursing Education Scholarship, vol. 18, no. 1, June 2021. Epmc, doi:10.1515/ijnes-2020-0068.
Walker JKL, Richard-Eaglin A, Hegde A, Muckler VC. A deep learning approach to student registered nurse anesthetist (SRNA) education. International journal of nursing education scholarship. 2021 Jun;18(1).
Journal cover image

Published In

International journal of nursing education scholarship

DOI

EISSN

1548-923X

ISSN

2194-5772

Publication Date

June 2021

Volume

18

Issue

1

Related Subject Headings

  • Thinking
  • Students, Nursing
  • Problem-Based Learning
  • Nursing
  • Nurse Anesthetists
  • Humans
  • Deep Learning
  • 4205 Nursing
  • 4204 Midwifery
  • 1302 Curriculum and Pedagogy