Data mining is a discipline devoted to scan data repositories, generate information and discover knowledge. It has the purpose to find data patterns, hidden relationships, association rules, classify objects, compose clusters of homogenous objects. In the context of education, data mining techniques have been recently used in the literature to explore and analyze both large repositories of data usually stored in the schools and universities databases for administrative purposes and large amounts of information generated in e-learning or web-based educational context. In this talk, the Educational Data Mining research area is briefly presented and some applications concerning students of the Computer Science degree course and of the Scientific degree courses of the University of Florence are illustrated. This kind of analysis can be used to better understand the performance of the student learning process and can give to university or school management some hints to improve the entire educational process.

Data Mining Techniques for Improving an Educational Process / D. Merlini, M. C. Verri. - ELETTRONICO. - (2019), pp. 0-0. (Intervento presentato al convegno ISPIM tenutosi a Firenze nel 16-19 giugno 2019).

Data Mining Techniques for Improving an Educational Process

D. Merlini;M. C. Verri
2019

Abstract

Data mining is a discipline devoted to scan data repositories, generate information and discover knowledge. It has the purpose to find data patterns, hidden relationships, association rules, classify objects, compose clusters of homogenous objects. In the context of education, data mining techniques have been recently used in the literature to explore and analyze both large repositories of data usually stored in the schools and universities databases for administrative purposes and large amounts of information generated in e-learning or web-based educational context. In this talk, the Educational Data Mining research area is briefly presented and some applications concerning students of the Computer Science degree course and of the Scientific degree courses of the University of Florence are illustrated. This kind of analysis can be used to better understand the performance of the student learning process and can give to university or school management some hints to improve the entire educational process.
2019
XXX ISPIM Innovation Conference - Celebrating Innovation - 500 Years Since Da Vinci
ISPIM
Firenze
D. Merlini, M. C. Verri
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1161087
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