%0 Conference Proceedings
%T Comparative Process Mining in Education: An Approach Based on Process Cubes
%+ Eindhoven University of Technology [Eindhoven] (TU/e)
%+ Vysšaja škola èkonomiki = National Research University Higher School of Economics [Moscow] (HSE)
%+ Fontys Hogescholen
%A Aalst, Wil
%A Guo, Shengnan
%A Gorissen, Pierre
%< avec comité de lecture
%( Lecture Notes in Business Information Processing
%B 3rd International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA)
%C Riva del Garda, Italy
%Y Paolo Ceravolo
%Y Rafael Accorsi
%Y Philippe Cudre-Mauroux
%I Springer Berlin Heidelberg
%3 Data-Driven Process Discovery and Analysis
%V LNBIP-203
%P 110-134
%8 2013-08-30
%D 2013
%K Process mining
%K Online analytical processing
%K Learning analytics
%K Comparative process mining
%Z Computer Science [cs]Conference papers
%X Process mining techniques enable the analysis of a wide variety of processes using event data. For example, event logs can be used to automatically learn a process model (e.g., a Petri net or BPMN model). Next to the automated discovery of the real underlying process, there are process mining techniques to analyze bottlenecks, to uncover hidden inefficiencies, to check compliance, to explain deviations, to predict performance, and to guide users towards “better” processes. Dozens (if not hundreds) of process mining techniques are available and their value has been proven in many case studies. However, existing techniques focus on the analysis of a single process rather than the comparison of different processes. In this paper, we propose comparative process mining using process cubes. An event has attributes referring to the dimensions of the process cube. Through slicing, dicing, rolling-up, and drilling-down we can view event data from different angles and produce process mining results that can be compared. To illustrate the process cube concept, we focus on educational data. In particular, we analyze data of students watching video lectures given by the first author. The dimensions of the process cube allow us to compare the process of students that passed the course versus the process of students that failed. We can also analyze differences between male and female students, between different parts of the course, and between Dutch students and international students. The initial analysis provided in this paper is used to elicit requirements for better tool support facilitating comparative process mining.
%G English
%Z TC 2
%Z WG 2.6
%Z WG 2.12
%2 https://inria.hal.science/hal-01746404/document
%2 https://inria.hal.science/hal-01746404/file/335156_1_En_6_Chapter.pdf
%L hal-01746404
%U https://inria.hal.science/hal-01746404
%~ IFIP
%~ IFIP-TC
%~ IFIP-LNBIP
%~ IFIP-TC2
%~ IFIP-WG2-6
%~ IFIP-SIMPDA
%~ IFIP-WG2-12
%~ IFIP-LNBIP-203