Learning analytics at UWB - first approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23420%2F18%3A43958718" target="_blank" >RIV/49777513:23420/18:43958718 - isvavai.cz</a>

Výsledek na webu

<a href="https://disconference.eu/wp-content/uploads/2017/01/DisCo-2018-Overcoming-the-Challenges-and-Barries-in-Open-Education-13th-conference-reader-1.pdf" target="_blank" >https://disconference.eu/wp-content/uploads/2017/01/DisCo-2018-Overcoming-the-Challenges-and-Barries-in-Open-Education-13th-conference-reader-1.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Learning analytics at UWB - first approach

Popis výsledku v původním jazyce

The focus of this paper is the first look and interpretation of learning analytics data from learning management system (LMS) at the University of West Bohemia in Pilsen (UWB). We claim that there are three types of granularity of LMS data. The first type is top-level, which describes approaches and usage of LMS as a whole. The second one is course-level, which deals with the behaviour and activities of all users as a whole on a specific course. And the last user-type, which interprets the activities of users in the course, and looks for common patterns of behaviour. This paper presents the first two types of granularity, based on real data from the university LMS. We are inspired by many previous studies focusing on learning systems of the LMS that often pay attention especially to academic success prediction or at-risk student identification (e.g. Smith et al. 2012, Jayaprakash et al., 2014, Baker et al., 2015). These findings form the basis for further research on identifying user behaviour on the course, and identifying students at risk of learning failure.

Název v anglickém jazyce

Learning analytics at UWB - first approach

Popis výsledku anglicky

The focus of this paper is the first look and interpretation of learning analytics data from learning management system (LMS) at the University of West Bohemia in Pilsen (UWB). We claim that there are three types of granularity of LMS data. The first type is top-level, which describes approaches and usage of LMS as a whole. The second one is course-level, which deals with the behaviour and activities of all users as a whole on a specific course. And the last user-type, which interprets the activities of users in the course, and looks for common patterns of behaviour. This paper presents the first two types of granularity, based on real data from the university LMS. We are inspired by many previous studies focusing on learning systems of the LMS that often pay attention especially to academic success prediction or at-risk student identification (e.g. Smith et al. 2012, Jayaprakash et al., 2014, Baker et al., 2015). These findings form the basis for further research on identifying user behaviour on the course, and identifying students at risk of learning failure.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50301 - Education, general; including training, pedagogy, didactics [and education systems]

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

DisCo 2018: Overcoming the Challenges and the Barriers in Open Education : 13 th conference reader

ISBN

978-80-86302-83-6

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

271-278

Název nakladatele

Centre for Higher Education Studies

Místo vydání

Praha

Místo konání akce

Praha

Datum konání akce

25. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000475841400024