Forecasting models in the state education system

Authors:
Gintautas Dzemyda;Vydunas Šaltenis;Vytautas Tiešis
Affiliations:
Vilnius Pedagogical University, Studentu, 39, LT-2004 Vilnius, Lithuania and Institute of Mathematics and Informatics, Adademijos 4, LT-2021 Vilnius, Lithuania;Vilnius Pedagogical University, Studentu, 39, LT-2004 Vilnius, Lithuania and Institute of Mathematics and Informatics, Adademijos 4, LT-2021 Vilnius, Lithuania;Vilnius Pedagogical University, Studentu, 39, LT-2004 Vilnius, Lithuania and Institute of Mathematics and Informatics, Adademijos 4, LT-2021 Vilnius, Lithuania
Venue:
Informatics in education
Year:
2003

Citing 1
Cited 1

Data mining: concepts and techniques

Data mining: concepts and techniques

Dimension Reduction and Data Visualization Using Neural Networks

Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents model-based assessment and forecasting of the Lithuanian education system in the period of 2001-2010. In order to obtain satisfactory forecasting results, constructing of models used for these aims should be grounded on some interactive data mining. Data mining of data stored in the system of the Lithuanian teacher's database and of data from other sources representing the state of education system and the demographic changes in Lithuania was used. The models cover the estimation of data quality in the databases, the analysis of flow of teachers and pupils, the clustering of schools, the model of dynamics of pedagogical staff and pupils, and the quality analysis of teachers. The main results of forecasting and integrated analysis of the Lithuanian teachers' database with other data reflecting the state of the education system and demographic changes in Lithuania are presented.