Determining students' academic failure profile founded on data mining methods
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...
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| creator | Bresfelean, Vasile Paul Bresfelean, Mihaela Ghisoiu, Nicolae Comes, Calin-Adrian |
| description | 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 students' 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 students' profile for exam failure/success. |
| doi_str_mv | 10.1109/ITI.2008.4588429 |
| format | Conference Proceeding |
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| identifier | ISSN: 1330-1012 |
| ispartof | ITI 2008 - 30th International Conference on Information Technology Interfaces, 2008, p.317-322 |
| issn | 1330-1012 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Applied sciences Classification algorithms classification learning clustering Clustering algorithms Computer science control theory systems Data mining Data processing. List processing. Character string processing Decision trees Exact sciences and technology FarthestFirst J48 Memory organisation. Data processing Partitioning algorithms Prediction algorithms Software Training |
| title | Determining students' academic failure profile founded on data mining methods |
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