Progressive Medical Simulation: An Analysis of the Integration of Progressive and Personalized Learning in Central Line Simulators

Progressive learning gradually increases task difficulty as students advance in their education. One area that can benefit from it is medical education since it can optimize medical trainees' skill acquisition. While progressive learning can allow for skill transfer to patient encounters, personalized learning increases the efficiency and effectiveness of learning. However, it is not well understood the number of practice trials needed to reach proficiency. To evaluate whether progressive and personalized learning can enhance medical trainees' learning gains, the learning interface of the Dynamic Haptic Robotic Trainer (DHRT) for Central Venous Catheterization was assessed. Results showed that residents' performance on the DHRT did not differ based on task difficulty and residents' performance was as effective with less number of trials. The findings imply a need to integrate progressive and personalized learning on the DHRT simulator to ensure that residents are fully prepared for any patient scenario in a real-life encounter.

Advisor: Dr.Scarlett Miller, Professor of Industrial Engineering and Engineering Design

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Work Title Progressive Medical Simulation: An Analysis of the Integration of Progressive and Personalized Learning in Central Line Simulators
Access
Open Access
Creators
  1. Isra K. Elsaadany
  2. Jessica M. Gonzalez-Vargas
  3. Jason Z. Moore
  4. Scarlett R. Miller
Keyword
  1. Medical simulation
  2. Progressive learning
  3. Personalized learning
  4. Skill acquisition
  5. Improving medical training
License In Copyright (Rights Reserved)
Work Type Research Paper
Acknowledgments
  1. This work was supported by National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) under Award No. ROHL127316. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Coauthors Dr. Moore and Miller owns equity in Medulate, which may have a future interest in this project. Company ownership has been reviewed by the University's Individual Conflict of Interest Committee and is currently being managed by the University.
Publication Date 2024
Deposited May 06, 2024

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Version 1
published

  • Created

    May 06, 2024 11:46 by ibe5049

  • Updated

    May 06, 2024 11:46 by [unknown user]

  • Updated Keyword, Description, Publication Date Show Changes

    May 06, 2024 11:55 by ibe5049

    Keyword
    • medical simulation, progressive learning, personalized learning, skill acquisition, improving medical training
    Description
    • Progressive learning gradually increases task difficulty as students advance in their education. One area that can benefit from it is medical education since it can optimize medical trainees' skill acquisition. While progressive learning can allow for skill transfer to patient encounters, personalized learning increases the efficiency and effectiveness of learning. However, it is not well understood the number of practice trials needed to reach proficiency. To evaluate whether progressive and personalized learning can enhance medical trainees' learning gains, the learning interface of the Dynamic Haptic Robotic Trainer (DHRT) for Central Venous Catheterization was assessed. Results showed that residents' performance on the DHRT did not differ based on task difficulty and residents' performance was as effective with less number of trials. The findings imply a need to integrate progressive and personalized learning on the DHRT simulator to ensure that residents are fully prepared for any patient scenario in a real-life encounter.
    • Advisor: Dr.Scarlett Miller, Professor of Industrial Engineering, scarlettmiller@psu.edu
    Publication Date
    • 2024
  • Updated Acknowledgments Show Changes

    May 06, 2024 11:58 by ibe5049

    Acknowledgments
    • This work was supported by National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) under Award No. ROHL127316. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Coauthors Dr. Moore and Miller owns equity in Medulate, which may have a future interest in this project. Company ownership has been reviewed by the University's Individual Conflict of Interest Committee and is currently being managed by the University.
  • Added Creator Isra Elsaadany

    May 06, 2024 11:58 by ibe5049

  • Added Creator Jessica Gonzalez-Vargas

    May 06, 2024 11:58 by ibe5049

  • Added Creator Jason Moore

    May 06, 2024 11:58 by ibe5049

  • Added Creator Scarlett Miller

    May 06, 2024 11:58 by ibe5049

  • Added ProgressiveMedicalSimulation.pdf

    May 06, 2024 11:58 by ibe5049

  • Updated Description, License Show Changes

    May 06, 2024 12:01 by ibe5049

    Description
    • Progressive learning gradually increases task difficulty as students advance in their education. One area that can benefit from it is medical education since it can optimize medical trainees' skill acquisition. While progressive learning can allow for skill transfer to patient encounters, personalized learning increases the efficiency and effectiveness of learning. However, it is not well understood the number of practice trials needed to reach proficiency. To evaluate whether progressive and personalized learning can enhance medical trainees' learning gains, the learning interface of the Dynamic Haptic Robotic Trainer (DHRT) for Central Venous Catheterization was assessed. Results showed that residents' performance on the DHRT did not differ based on task difficulty and residents' performance was as effective with less number of trials. The findings imply a need to integrate progressive and personalized learning on the DHRT simulator to ensure that residents are fully prepared for any patient scenario in a real-life encounter.
    • Advisor: Dr.Scarlett Miller, Professor of Industrial Engineering, scarlettmiller@psu.edu
    • Advisor: Dr.Scarlett Miller, Professor of Industrial Engineering and Engineering Design
    License
    • https://rightsstatements.org/page/InC/1.0/
  • Published

    May 06, 2024 12:01 by ibe5049

  • Updated

    May 06, 2024 22:03 by [unknown user]

  • Updated Work Title Show Changes

    May 09, 2024 09:33 by avs5190

    Work Title
    • PROGRESSIVE MEDICAL SIMULATION: AN ANALYSIS OF THE INTEGRATION OF PROGRESSIVE AND PERSONALIZED LEARNING IN CENTRAL LINE SIMULATORS
    • Progressive Medical Simulation: An Analysis of the Integration of Progressive and Personalized Learning in Central Line Simulators
  • Updated Keyword Show Changes

    May 09, 2024 09:33 by avs5190

    Keyword
    • medical simulation, progressive learning, personalized learning, skill acquisition, improving medical training
    • Medical simulation, Progressive learning, Personalized learning, Skill acquisition, Improving medical training
  • Renamed Creator Isra K. Elsaadany Show Changes

    May 09, 2024 09:34 by avs5190

    • Isra Elsaadany
    • Isra K. Elsaadany
  • Renamed Creator Jessica M. Gonzalez-Vargas Show Changes

    May 09, 2024 09:34 by avs5190

    • Jessica Gonzalez-Vargas
    • Jessica M. Gonzalez-Vargas
  • Renamed Creator Jason Z. Moore Show Changes

    May 09, 2024 09:34 by avs5190

    • Jason Moore
    • Jason Z. Moore
  • Renamed Creator Scarlett R. Miller Show Changes

    May 09, 2024 09:34 by avs5190

    • Scarlett Miller
    • Scarlett R. Miller