Improving Learning System Performance with Multimedia Semantics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00115180" target="_blank" >RIV/00216224:14330/20:00115180 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICSC.2020.00050" target="_blank" >http://dx.doi.org/10.1109/ICSC.2020.00050</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICSC.2020.00050" target="_blank" >10.1109/ICSC.2020.00050</a>
Alternative languages
Result language
angličtina
Original language name
Improving Learning System Performance with Multimedia Semantics
Original language description
Nowadays, different new learning methodologies have been proposed to achieve effective learning in University education. One of the most promising methodologies for teaching computer science is multimedia-based education. In order to empower the performance within the online learning platforms, such as Moodle or OLE, this paper proposes to integrate the multimedia-based education to learning systems, and conducts an experiment with the operating system course. We show that exploiting multimedia, such as educational video and smart text, can significantly improve the student's learning performance in terms of exam grade and knowledge transfer. Further, the paper presents a real-world case study depicting how to enhance the performance of learning platform with multimedia semantics.
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
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
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 14th IEEE International Conference on Semantic Computing
ISBN
9781728163321
ISSN
2325-6516
e-ISSN
—
Number of pages
4
Pages from-to
238-241
Publisher name
IEEE
Place of publication
San Diego, California, USA
Event location
San Diego, California, USA
Event date
Jan 1, 2020
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000565450400041