Applying perceptual and adaptive learning techniques for teaching introductory histopathology

Background: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive scie...

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Main Authors: Sally Krasne, Joseph D Hillman, Philip J Kellman, Thomas A Drake
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2013-01-01
Series:Journal of Pathology Informatics
Subjects:
Online Access:http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=34;epage=34;aulast=Krasne
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spelling doaj-5e8dcf8a4fe849daa6318dd6912bc5322020-11-24T23:13:32ZengWolters Kluwer Medknow PublicationsJournal of Pathology Informatics2153-35392153-35392013-01-0141343410.4103/2153-3539.123991Applying perceptual and adaptive learning techniques for teaching introductory histopathologySally KrasneJoseph D HillmanPhilip J KellmanThomas A DrakeBackground: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem. Methods: We adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses) that appear during a learning session based on each learner′s accuracy and response time (RT). We developed a perceptual and adaptive learning module (PALM) that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a "Score" that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness. Results: Accuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1 st -year students, but not significantly so for 2 nd -year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1 st and 2 nd year students suggesting good retention of pattern recognition. Student evaluations were very favorable. Conclusion: A web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students.http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=34;epage=34;aulast=KrasneCognitive sciencedermatologymedical educationpathologyperceptual learning
collection DOAJ
language English
format Article
sources DOAJ
author Sally Krasne
Joseph D Hillman
Philip J Kellman
Thomas A Drake
spellingShingle Sally Krasne
Joseph D Hillman
Philip J Kellman
Thomas A Drake
Applying perceptual and adaptive learning techniques for teaching introductory histopathology
Journal of Pathology Informatics
Cognitive science
dermatology
medical education
pathology
perceptual learning
author_facet Sally Krasne
Joseph D Hillman
Philip J Kellman
Thomas A Drake
author_sort Sally Krasne
title Applying perceptual and adaptive learning techniques for teaching introductory histopathology
title_short Applying perceptual and adaptive learning techniques for teaching introductory histopathology
title_full Applying perceptual and adaptive learning techniques for teaching introductory histopathology
title_fullStr Applying perceptual and adaptive learning techniques for teaching introductory histopathology
title_full_unstemmed Applying perceptual and adaptive learning techniques for teaching introductory histopathology
title_sort applying perceptual and adaptive learning techniques for teaching introductory histopathology
publisher Wolters Kluwer Medknow Publications
series Journal of Pathology Informatics
issn 2153-3539
2153-3539
publishDate 2013-01-01
description Background: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem. Methods: We adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses) that appear during a learning session based on each learner′s accuracy and response time (RT). We developed a perceptual and adaptive learning module (PALM) that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a "Score" that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness. Results: Accuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1 st -year students, but not significantly so for 2 nd -year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1 st and 2 nd year students suggesting good retention of pattern recognition. Student evaluations were very favorable. Conclusion: A web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students.
topic Cognitive science
dermatology
medical education
pathology
perceptual learning
url http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=34;epage=34;aulast=Krasne
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AT philipjkellman applyingperceptualandadaptivelearningtechniquesforteachingintroductoryhistopathology
AT thomasadrake applyingperceptualandadaptivelearningtechniquesforteachingintroductoryhistopathology
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