This paper presents a data mining methodology to analyze the careers of students, where a career can be seen as a sequence of exams. The model is built using sequential pattern analysis and uses the algorithm SPAM. We consider an ideal career corresponding to a student which has taken each examination just after the end of the corresponding course, without delays. The frequent patterns identified by the sequential pattern analysis are then compared with the career of the ideal student. The most interesting patterns are then used to refine the analysis by using clustering techniques. Finally, we apply this methodology to a real case study and interprete the results.
Sequential patterns analysis in a student database / R. Campagni; D. Merlini; R. Sprugnoli. - ELETTRONICO. - (2012), pp. 1-16. (Intervento presentato al convegno ECML-PKDD Workshop: Mining and exploiting interpretable local patterns (I-Pat 2012) tenutosi a Bristol, UK nel September, 24-28).
Sequential patterns analysis in a student database
CAMPAGNI, RENZA;MERLINI, DONATELLA;SPRUGNOLI, RENZO
2012
Abstract
This paper presents a data mining methodology to analyze the careers of students, where a career can be seen as a sequence of exams. The model is built using sequential pattern analysis and uses the algorithm SPAM. We consider an ideal career corresponding to a student which has taken each examination just after the end of the corresponding course, without delays. The frequent patterns identified by the sequential pattern analysis are then compared with the career of the ideal student. The most interesting patterns are then used to refine the analysis by using clustering techniques. Finally, we apply this methodology to a real case study and interprete the results.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.