Authors:
John Garofalakis
;
Antonios Maritsas
and
Flora Oikonomou
Affiliation:
University of Patras, Greece
Keyword(s):
Educational Data Mining, Geographic Information Systems, Visualization, Decision Support, Clustering, Classification, Epidemy Spread.
Related
Ontology
Subjects/Areas/Topics:
Classroom Management
;
Computer-Supported Education
;
Information Technologies Supporting Learning
Abstract:
Educational Data Mining (EDM) has emerged as an interdisciplinary research area that applies Data Mining
(DM) techniques to educational data in order to discover novel and potentially useful information. On the
other hand, Geographic Information Systems (GIS) are ones designed to manage spatial data and related
attributes and can be used for assisting decision support. This paper proposes an innovative use of DM and
visualization GIS techniques for decision support in planning and management of Greek public education
focused on high risk groups such as young children. The developed application clusters school units with
similar features, such as students’ and teachers’ absences, and represents them on a map, enabling user to
make decisions being aware of geographical information. Afterwards, based on real data stored during
epidemic spread periods, such as the H1N1 flu pandemic during 2009, the application predicts whether a
school should be opened or closed considering students’ and
teachers’ absences of a specific time interval.
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