Pitfalls in users' evaluation of algorithms for text-based similarity detection in medical education
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F18%3A00104404" target="_blank" >RIV/00216224:14110/18:00104404 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8490018" target="_blank" >https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8490018</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Pitfalls in users' evaluation of algorithms for text-based similarity detection in medical education
Original language description
This paper introduces a user evaluation of several approaches for an automated similarity detection between study materials and curriculum description in the field of medical and healthcare education. Our objective is to present an effective methodology of getting relevant feedback from medical students and teachers. Two various data sets (electronic study materials represented by interactive educational algorithms on the AKUTNE.CZ platform and the curriculum of the General Medicine study programme) are processed. For the purposes of this work, text similarity between two data sets is expressed lexically, i.e. character-based (n-gram) similarity as well as term-based similarity methods are used. We present the comparison of five selected approaches to similarity calculation as well as an objective discussion covering our experience with and pitfalls of user evaluation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
PROCEEDINGS OF THE 2018 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS)
ISBN
9788394941956
ISSN
2325-0348
e-ISSN
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Number of pages
8
Pages from-to
109-116
Publisher name
IEEE
Place of publication
New York
Event location
Poznan
Event date
Sep 9, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000454652300017