University degrees are typically organized in courses with prerequisites among them. If prerequisite are not mandatory, students are left free to attend courses and take exams in almost any order. While favoring flexible organization of the work by students, this practice can also lead to unstructured learning practices and to performance issues. In this paper we propose to take a process-oriented view of students' careers and analyze them by process mining techniques. Results provide us with some evidence of typical patterns followed by students and of the advantages of adopting structured learning practices.
Students' careers analysis: A process mining approach / Cameranesi, Marco; Diamantini, Claudia; Genga, Laura; Potena, Domenico. - (2017). (Intervento presentato al convegno International Conference on Web Intelligence, Mining and Semantics, WIMS 2017 tenutosi a Amantea, Italy nel June 19 - 22, 2017) [10.1145/3102254.3102270].
Students' careers analysis: A process mining approach
Cameranesi Marco;Diamantini Claudia;Genga Laura;Potena Domenico
2017-01-01
Abstract
University degrees are typically organized in courses with prerequisites among them. If prerequisite are not mandatory, students are left free to attend courses and take exams in almost any order. While favoring flexible organization of the work by students, this practice can also lead to unstructured learning practices and to performance issues. In this paper we propose to take a process-oriented view of students' careers and analyze them by process mining techniques. Results provide us with some evidence of typical patterns followed by students and of the advantages of adopting structured learning practices.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
