Title :
Determining students’ academic failure profile founded on data mining methods
Author :
Bresfelean, Vasile Paul ; Bresfelean, Mihaela ; Ghisoiu, Nicolae ; Comes, Calin-Adrian
Author_Institution :
Fac. of Econ. & Bus. Adm., Babes-Bolyai Univ., Cluj-Napoca
Abstract :
Exams failure among university students has long fed a large number of debates, many education experts seeking to comprehend and explicate it, and many statisticians have tried to predict it. Understanding, predicting and preventing the academic failure are complex and continuous processes anchored in past and present information collected from scholastic situations and studentspsila surveys, but also on scientific research based on data mining technologies. In the current article the authors illustrate their experiments in the educational area, based on classification learning and data clustering techniques, made in order to draw up the studentspsila profile for exam failure/success.
Keywords :
data mining; educational administrative data processing; learning (artificial intelligence); pattern classification; pattern clustering; classification learning; data clustering technique; data mining method; student academic failure profile determination; university exam failure; Clustering algorithms; Clustering methods; Data mining; Economic forecasting; Education; Educational programs; Knowledge management; Partitioning algorithms; Technology management; Testing; Data mining; FarthestFirst; J48; classification learning; clustering;
Conference_Titel :
Information Technology Interfaces, 2008. ITI 2008. 30th International Conference on
Conference_Location :
Dubrovnik
Print_ISBN :
978-953-7138-12-7
Electronic_ISBN :
1330-1012
DOI :
10.1109/ITI.2008.4588429
