Visit rate analysis of course activities: Case study

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Visit rate analysis of course activities: Case study

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Visit rate analysis of course activities: Case study

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ICETA 2015 - 13th IEEE International Conference on Emerging eLearning Technologies and Applications : Proceedings

ISBN

978-1-4673-8534-3

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

1-6

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Starý Smokovec

Datum konání akce

26. 11. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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