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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">INFORMATICA</journal-id><journal-title-group><journal-title>Informatica</journal-title></journal-title-group><issn pub-type="epub">0868-4952</issn><issn pub-type="ppub">0868-4952</issn><publisher><publisher-name>VU</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">INF13408</article-id><article-id pub-id-type="doi">10.3233/INF-2002-13408</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research article</subject></subj-group></article-categories><title-group><article-title>Quantitative Forecasting and Assessment Models in the State Education System</article-title></title-group><contrib-group><contrib contrib-type="Author"><name><surname>Šaltenis</surname><given-names>Vydūnas</given-names></name><email xlink:href="mailto:saltenis@ktl.mii.lt">saltenis@ktl.mii.lt</email><xref ref-type="aff" rid="j_INFORMATICA_aff_000"/></contrib><contrib contrib-type="Author"><name><surname>Dzemyda</surname><given-names>Gintautas</given-names></name><email xlink:href="mailto:dzemyda@ktl.mii.lt">dzemyda@ktl.mii.lt</email><xref ref-type="aff" rid="j_INFORMATICA_aff_001"/><xref ref-type="aff" rid="j_INFORMATICA_aff_002"/></contrib><contrib contrib-type="Author"><name><surname>Tiešis</surname><given-names>Vytautas</given-names></name><email xlink:href="mailto:tiesis@ktl.mii.lt">tiesis@ktl.mii.lt</email><xref ref-type="aff" rid="j_INFORMATICA_aff_001"/><xref ref-type="aff" rid="j_INFORMATICA_aff_002"/></contrib><aff id="j_INFORMATICA_aff_000">Institute of Mathematics and Informatics, Akademijos 4, LT-2021 Vilnius, Lithuania</aff><aff id="j_INFORMATICA_aff_001">Vilnius Pedagogical University, Studentų 39, LT-2004 Vilnius, Lithuania</aff><aff id="j_INFORMATICA_aff_002">Institute of Mathematics and Informatics, Akademijos 4, LT-2021 Vilnius, Lithuania</aff></contrib-group><pub-date pub-type="epub"><day>01</day><month>01</month><year>2002</year></pub-date><volume>13</volume><issue>4</issue><fpage>485</fpage><lpage>500</lpage><history><date date-type="received"><day>01</day><month>06</month><year>2002</year></date></history><abstract><p>This paper presents model-based forecasting of the Lithuanian education system in the period of 2001–2010. In order to obtain satisfactory forecasting results, development of models used for these aims should be grounded on some interactive data mining. The process of the development is usually accompanied by the formulation of some assumptions to background methods or models. The accessibility and reliability of data sources should be verified. Special data mining of data sources may verify the assumptions. Interactive data mining of the data, stored in the system of the Lithuanian teachers' database, and that of other sources representing the state of the education system and demographic changes in Lithuania was used. The models cover the estimation of data quality in the databases, analysis of the flow of teachers and pupils, clustering of schools, the model of dynamics of the 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.</p></abstract><kwd-group><label>Keywords</label><kwd>modelling</kwd><kwd>data mining</kwd><kwd>neural networks</kwd><kwd>clustering</kwd><kwd>forecasting</kwd><kwd>education system</kwd></kwd-group></article-meta></front></article>