Další formáty:
BibTeX
LaTeX
RIS
@inproceedings{1196467,
author = {Géryk, Jan and Popelínský, Lubomír},
address = {London, United Kingdom},
booktitle = {Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014)},
editor = {John Stamper, Zachary Pardos, Manolis Mavrikis, and Bruce M. McLaren (Eds.)},
keywords = {student retention; student drop-out; visual analytics; motion charts; animation},
howpublished = {elektronická verze "online"},
language = {eng},
location = {London, United Kingdom},
isbn = {978-0-9839525-4-1},
pages = {331-332},
publisher = {International Educational Data Mining Society},
title = {Analysis of Student Retention and Drop-out using Visual Analytics},
year = {2014}
}
TY - JOUR
ID - 1196467
AU - Géryk, Jan - Popelínský, Lubomír
PY - 2014
TI - Analysis of Student Retention and Drop-out using Visual Analytics
PB - International Educational Data Mining Society
CY - London, United Kingdom
SN - 9780983952541
KW - student retention
KW - student drop-out
KW - visual analytics
KW - motion charts
KW - animation
N2 - 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 quite beneficial, there are types of questions that cannot be examined using them. Since the questions involve quantitative relationship other than change through time.
ER -
GÉRYK, Jan a Lubomír POPELÍNSKÝ. Analysis of Student Retention and Drop-out using Visual Analytics. In John Stamper, Zachary Pardos, Manolis Mavrikis, and Bruce M. McLaren (Eds.). \textit{Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014)}. London, United Kingdom: International Educational Data Mining Society. s.~331-332. ISBN~978-0-9839525-4-1. 2014.
|
