Comparison of self-directed learning versus instructor-modeled learning during a simulated clinical experience

Judy L. LeFlore, Mindi Anderson, Jacqueline L. Michael, William D. Engle, Jo Dee Anderson

Research output: Contribution to journalArticle

58 Scopus citations

Abstract

BACKGROUND: There are no reports in the literature that compare instructor-modeled learning to self-directed learning when simulation is used. Therefore, no evidence exists to know which approach is superior. This study aims to test the hypothesis that instructor-modeled learning is more effective compared with self-directed learning during a simulated clinical experience. METHODS: This is a descriptive pilot study to compare instructor-modeled learning with self-directed learning during a clinical simulated experience. Four evaluation tools were used at three time points to evaluate knowledge, self-efficacy (self confidence), and behaviors. RESULTS: Sixteen students participated. There were no statistically significant differences between the groups on the Knowledge Assessment Test. There were significant differences between the groups in the Self-Efficacy Tool (SET) at three times (time 1: P = 0.006, time 2: P = 0.008, time 3: P = 0.012). The only significance between the groups on the Technical Evaluation Tool was time to start Albuterol. The Behavioral Assessment Tool (BAT) showed significant differences between the groups in 8 out of 10 components of the tool. A strong correlation was observed between the overall score of the BAT and the SET Score. CONCLUSION: Although the small sample size prohibits definitive conclusions, the data suggest that instructor-modeled learning may be more effective than self-directed learning for some aspects of learning during a clinical simulated experience.

Original languageEnglish (US)
Pages (from-to)170-177
Number of pages8
JournalSimulation in Healthcare
Volume2
Issue number3
DOIs
StatePublished - Sep 1 2007

ASJC Scopus subject areas

  • Epidemiology
  • Medicine (miscellaneous)
  • Education
  • Modeling and Simulation

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