Literature DB >> 8947617

An intelligent learning environment for advanced cardiac life support.

C R Eliot1, K A Williams, B P Woolf.   

Abstract

Resuscitation from clinical cardiac arrest is complex and often takes several years to learn. This paper describes an intelligent simulation-based tutor for ACLS which increases students' opportunity to practice before, during and after the ACLS course, thus bridging the gap between studying theory and didactic textbook material and working with patients. Sophisticated reasoning about student performance, compared to an expert model, distinguishes this system from other computerized instruction systems. Intelligence in the tutor allows the system to make the simulation dynamically adaptive to focus on areas where the student's learning needs are greatest. A formative evaluation with two classes of fourth year medical students suggested that the tutor was helpful, realistic and effective. Positive reactions and strong student involvement with the simulation suggest that this simulation-based tutor may improve learning and retention while decreasing anxiety for most students.

Entities:  

Mesh:

Year:  1996        PMID: 8947617      PMCID: PMC2232984     

Source DB:  PubMed          Journal:  Proc AMIA Annu Fall Symp        ISSN: 1091-8280


  4 in total

Review 1.  Application of teaching and learning principles to computer-aided instruction.

Authors:  F R Jelovsek; V A Catanzarite; R D Price; R E Stull
Journal:  MD Comput       Date:  1989 Sep-Oct

Review 2.  Computer-assisted learning and evaluation in medicine.

Authors:  T E Piemme
Journal:  JAMA       Date:  1988-07-15       Impact factor: 56.272

3.  Funding for computer-assisted instruction projects.

Authors:  M Corn
Journal:  Acad Med       Date:  1994-12       Impact factor: 6.893

4.  Education in adult advanced cardiac life support training programs: changing the paradigm. Members of the Advanced Cardiac Life Support Education Panel.

Authors:  J E Billi; G E Membrino
Journal:  Ann Emerg Med       Date:  1993-02       Impact factor: 5.721

  4 in total
  6 in total

1.  A general architecture for intelligent tutoring of diagnostic classification problem solving.

Authors:  Rebecca S Crowley; Olga Medvedeva
Journal:  AMIA Annu Symp Proc       Date:  2003

2.  Evaluation of an intelligent tutoring system in pathology: effects of external representation on performance gains, metacognition, and acceptance.

Authors:  Rebecca S Crowley; Elizabeth Legowski; Olga Medvedeva; Eugene Tseytlin; Ellen Roh; Drazen Jukic
Journal:  J Am Med Inform Assoc       Date:  2007-01-09       Impact factor: 4.497

3.  Adapting web-based instruction to residents' knowledge improves learning efficiency: a randomized controlled trial.

Authors:  David A Cook; Thomas J Beckman; Kris G Thomas; Warren G Thompson
Journal:  J Gen Intern Med       Date:  2008-07       Impact factor: 5.128

4.  Simulation-Based Cryosurgery Intelligent Tutoring System Prototype.

Authors:  Anjali Sehrawat; Robert Keelan; Kenji Shimada; Dona M Wilfong; James T McCormick; Yoed Rabin
Journal:  Technol Cancer Res Treat       Date:  2015-05-03

5.  Modeling emotion and behavior in animated personas to facilitate human behavior change: the case of the HEART-SENSE game.

Authors:  B G Silverman; J Holmes; S Kimmel; C Branas; D Ivins; R Weaver; Y Chen
Journal:  Health Care Manag Sci       Date:  2001-09

6.  Simulation-Based Cryosurgery Training: Variable Insertion Depth Planning in Prostate Cryosurgery.

Authors:  Anjali Sehrawat; Robert Keelan; Kenji Shimada; Dona M Wilfong; James T McCormick; Yoed Rabin
Journal:  Technol Cancer Res Treat       Date:  2015-11-06
  6 in total

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