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A two-step clustering approach for improving educational process model discovery

Ariouat, Hanane and Cairns, Awatef Hicheur and Barkaoui, Kamel and Akoka, Jacky and Khelifa, Nasser A two-step clustering approach for improving educational process model discovery. (2016) In: 25th IEEE International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE 2016), 13 June 2016 - 15 June 2016 (Paris, France).

(Document in English)

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Official URL: http://dx.doi.org/10.1109/WETICE.2016.18


Process mining refers to the extraction of process models from event logs. As real-life processes tend to be less structured and more flexible, clustering techniques are used to divide traces into clusters, such that similar types of behavior are grouped in the cluster. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to better understand students' learning habits and the factors influencing their performance. However, the obtained models, usually, cannot fit well to the general students' behaviour and can be too large and complex for use or analysis by an instructor. These models are called spaghetti models. In the present work, we propose to use a two steps-based approach of clustering to improve educational process mining. The first step consist of creating clusters based employability indicators and the second step consist on clustering the obtained clusters using the AXOR algorithm which is based on traces profiles in order to refine the obtained results from the first step. We have experimented this approach using the tool ProM Framework and we have found that this approach optimizes at the same time, both the performance/suitability and comprehensibility/size of the obtained model.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org This papers appears in Proceedings of WETICE 2016 Electronic ISBN: 978-1-5090-1663-1 The original PDF of the article can be found at: http://ieeexplore.ieee.org/document/7536427/ Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
HAL Id:hal-01500511
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Other partners > ALTRAN (FRANCE)
Other partners > Conservatoire National des Arts et Métiers - CNAM (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Deposited On:16 Mar 2017 11:06

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