Literature DB >> 24084310

Adaptive and perceptual learning technologies in medical education and training.

Philip J Kellman1.   

Abstract

Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint &
Copyright © 2013 Association of Military Surgeons of the U.S.

Entities:  

Mesh:

Year:  2013        PMID: 24084310     DOI: 10.7205/MILMED-D-13-00218

Source DB:  PubMed          Journal:  Mil Med        ISSN: 0026-4075            Impact factor:   1.437


  14 in total

1.  Mastering Electrocardiogram Interpretation Skills Through a Perceptual and Adaptive Learning Module.

Authors:  Sally Krasne; Carl D Stevens; Philip J Kellman; James T Niemann
Journal:  AEM Educ Train       Date:  2020-05-05

2.  Adaptive response-time-based category sequencing in perceptual learning.

Authors:  Everett Mettler; Philip J Kellman
Journal:  Vision Res       Date:  2013-12-29       Impact factor: 1.886

3.  The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes.

Authors:  Carolyn A Bufford; Everett Mettler; Emma H Geller; Philip J Kellman
Journal:  Cogsci       Date:  2014-07

4.  Evaluating the Use of Supplemental Training Technologies in Dermatology Education.

Authors:  Mallory M Aycock; Craig D Marker; Philip J Kellman
Journal:  J Dermatol Physician Assist       Date:  2021

5.  Effect of a Mobile Web App on Kidney Transplant Candidates' Knowledge About Increased Risk Donor Kidneys: A Randomized Controlled Trial.

Authors:  Elisa J Gordon; Min-Woong Sohn; Chih-Hung Chang; Gwen McNatt; Karina Vera; Nicole Beauvais; Emily Warren; Roslyn B Mannon; Michael G Ison
Journal:  Transplantation       Date:  2017-06       Impact factor: 4.939

6.  Towards a whole brain model of Perceptual Learning.

Authors:  Marcello Maniglia; Aaron R Seitz
Journal:  Curr Opin Behav Sci       Date:  2017-12-13

7.  Applying perceptual and adaptive learning techniques for teaching introductory histopathology.

Authors:  Sally Krasne; Joseph D Hillman; Philip J Kellman; Thomas A Drake
Journal:  J Pathol Inform       Date:  2013-12-31

8.  Adaptive Learning in Medical Education: The Final Piece of Technology Enhanced Learning?

Authors:  Neel Sharma; Iain Doherty; Chaoyan Dong
Journal:  Ulster Med J       Date:  2017-09-12

9.  Does self-modulated learning vs. algorithm-regulated learning of dermatology morphology affect learning efficiency of medical students?

Authors:  Danya Traboulsi; Jori Hardin; Laurie Parsons; Jason Waechter
Journal:  Can Med Educ J       Date:  2019-07-24

10.  Perceptual Learning of Appendicitis Diagnosis in Radiological Images.

Authors:  Ian Andrew Johnston; Mohan Ji; Aaron Cochrane; Zachary Demko; Jessica B Robbins; Jason W Stephenson; C Shawn Green
Journal:  J Vis       Date:  2020-08-03       Impact factor: 2.240

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