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

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....

Descripción completa

Detalles Bibliográficos
Publicado en:International Journal of Nursing Education Scholarship Vol. 18; no. 1; pp. 1 - 9
Autores principales: Walker, Julia K. L., Richard-Eaglin, Angela, Hegde, Akhil, Muckler, Virginia C.
Formato: research tables/charts Journal Article
Publicado: De Gruyter 2021
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154078770&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 154078770
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        1548923X
        YRZ
      jtl: International Journal of Nursing Education Scholarship
      issn: 1548923X
      maglogo: N
    pubinfo:
      dt: 2021
      vid: 18
      iid: 1
      pid: 1734
      pub: De Gruyter
      place: , <Blank>
    artinfo:
      ui:
        154078770
        154078770
        154078770
        10.1515/ijnes-2020-0068
        154078770
      ppf: 1
      ppct: 8
      formats:
      tig:
        atl: A deep learning approach to student registered nurse anesthetist (SRNA) education.
      aug:
        au:
          Walker, Julia K. L.
          Richard-Eaglin, Angela
          Hegde, Akhil
          Muckler, Virginia C.
        affil: Duke University School of Nursing, Durham, NC, 27710, USA
      sug:
        subj:
          Deep Learning
          Critical Thinking
          Problem-Based Learning
          Students, Nursing
          Education, Nurse Anesthesia
          Student Attitudes
          Human
          Male
          Female
          Descriptive Statistics
          Male
          Female
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N