Analysis of Student Retention and Drop-out using Visual Analytics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00076278" target="_blank" >RIV/00216224:14330/14:00076278 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Analysis of Student Retention and Drop-out using Visual Analytics
Original language description
In the paper, we have described the motivation and design of the VA tool EDAIME which is intended for exploratory analysis of educational data. We enhanced the concept of Motion Charts and successfully expanded it to be more suitable for such analyses. We have successfully employed it to verify the suggested hypothesis. A further in-depth analysis with different mapping of variables is needed to quantify the correlations more accurately. Despite the fact that common data visualization methods are quitebeneficial, there are types of questions that cannot be examined using them. Since the questions involve quantitative relationship other than change through time.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
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 7th International Conference on Educational Data Mining (EDM 2014)
ISBN
9780983952541
ISSN
—
e-ISSN
—
Number of pages
2
Pages from-to
331-332
Publisher name
International Educational Data Mining Society
Place of publication
London, United Kingdom
Event location
London, United Kingdom
Event date
Jan 1, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—