Detecting Disengagement of Online Students through Log Files Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10287120" target="_blank" >RIV/00216208:11320/14:10287120 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11140/14:10287120

Výsledek na webu

<a href="http://conference.pixel-online.net/FOE/prevedition.php?id_edition=6&mat=CPR" target="_blank" >http://conference.pixel-online.net/FOE/prevedition.php?id_edition=6&mat=CPR</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Detecting Disengagement of Online Students through Log Files Analysis

Popis výsledku v původním jazyce

To achieve effective learning, motivational aspects like engagement play a very important role. Within online learning applications the disengagement detection and prediction based on real data (not always in real time) is becoming more and more popularamong educational specialists. Many Elearning systems, and virtual or remote learning environments, could be improved by tracking students' disengagement that, in turn, would allow personalized interventions at appropriate times in order to re-engage students. The present article describes the results of a medium-scale (N = 56) study, using log files from Open Remote Laboratory at Charles University in Prague, Faculty of Mathematics and Physics, to observe secondary school students' behaviour during their work in virtual environment. Simple data mining and text mining techniques were used to reveal individual user's behavioural patterns and to detect disengagement. The results will be used mainly to improve the systems' adaptability to

Název v anglickém jazyce

Detecting Disengagement of Online Students through Log Files Analysis

Popis výsledku anglicky

To achieve effective learning, motivational aspects like engagement play a very important role. Within online learning applications the disengagement detection and prediction based on real data (not always in real time) is becoming more and more popularamong educational specialists. Many Elearning systems, and virtual or remote learning environments, could be improved by tracking students' disengagement that, in turn, would allow personalized interventions at appropriate times in order to re-engage students. The present article describes the results of a medium-scale (N = 56) study, using log files from Open Remote Laboratory at Charles University in Prague, Faculty of Mathematics and Physics, to observe secondary school students' behaviour during their work in virtual environment. Simple data mining and text mining techniques were used to reveal individual user's behavioural patterns and to detect disengagement. The results will be used mainly to improve the systems' adaptability to

Druh

D - Stať ve sborníku

CEP obor

AM - Pedagogika a školství

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

International conference The future of Education Edition 4

ISBN

978-88-6292-499-3

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

137-141

Název nakladatele

Libreriauniversitaria.it

Místo vydání

Florence, Italy

Místo konání akce

Florence Italy

Datum konání akce

12. 6. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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