Visit rate analysis of course activities: Case study
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F15%3A39902626" target="_blank" >RIV/00216275:25410/15:39902626 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICETA.2015.7558507" target="_blank" >http://dx.doi.org/10.1109/ICETA.2015.7558507</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICETA.2015.7558507" target="_blank" >10.1109/ICETA.2015.7558507</a>
Alternative languages
Result language
angličtina
Original language name
Visit rate analysis of course activities: Case study
Original language description
One of the most important areas of optimizing the learning environment in distance education is to analyze the behavior of students in eLearning courses. The aim of the paper is to summarize the field of Educational data mining, analyze the behavior of students in e-course Computer data analysis and to present a few cases of a similar analysis of the behavior of students. The results of the analysis may have potential for future use in optimizing the e-course. Analysis results were obtained using extracted association rules from the e-course. This electronic course is designed to use linear and branched teaching programs. Target group research were students of Computer Science, which was reflected in the results. It is not necessary to have special knowledge of IT to work in e-course. The course was created using LMS Moodle, which records the behaviour of users to the database. We used specific types of data, which indicate user traffic on every single page of the course. We used the log file containing records with the behavior of 69 students in e-course. Session identification is for the distribution of accesses of all users of e-course to separated sessions. Students are identified by their login ID. Therefore, we can separate the users who share a computer. Students who have used e-course Computer data analysis, were successful in the final test. By analyzing we can improve e-course. After implementation of necessary changes we can evaluate impact of these changes in the efficacy of the course.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICETA 2015 - 13th IEEE International Conference on Emerging eLearning Technologies and Applications : Proceedings
ISBN
978-1-4673-8534-3
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1-6
Publisher name
IEEE (Institute of Electrical and Electronics Engineers)
Place of publication
New York
Event location
Starý Smokovec
Event date
Nov 26, 2015
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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