CBR-Mining Approach to Improve Learning System Engineering in a Collaborative E-Learning Platform

Fatima Zahra Berriche, Besma Zeddini, Hubert Kadima, Alain Riviere

2018

Abstract

System engineering (SE) is an approach that involves customers and users in the development process and more particularly during the definition of requirements and system functionalities. In order to meet the challenges and increasing complexity of system engineering, the training of engineering students in this field is necessary. It enables learners to acquire sound theoretical and practical knowledge, and to adapt to the majority of profiles of the position related to system engineering field proposed by industrial companies. In this paper, we present a continuity of our research work (Berriche et al., 2015), we study the feasibility of the CBR-mining (case based reasoning and process mining) approach in the context of our platform dedicated to the learning of system engineering. First, we apply the CBR-mining approach to monitor student interactions from log files. Secondly, we propose clusters that bring together all the educational processes most performed by students. We have experimented this approach using the ProM Framework.

Paper Citation

in Harvard Style

Berriche F., Zeddini B., Kadima H. and Riviere A. (2018). CBR-Mining Approach to Improve Learning System Engineering in a Collaborative E-Learning Platform.In Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS, ISBN 978-989-758-297-4, pages 94-101. DOI: 10.5220/0006693200940101

in Bibtex Style

@conference{complexis18,
author={Fatima Zahra Berriche and Besma Zeddini and Hubert Kadima and Alain Riviere},
title={CBR-Mining Approach to Improve Learning System Engineering in a Collaborative E-Learning Platform},
booktitle={Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS,},
year={2018},
pages={94-101},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006693200940101},
isbn={978-989-758-297-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS,
TI - CBR-Mining Approach to Improve Learning System Engineering in a Collaborative E-Learning Platform
SN - 978-989-758-297-4
AU - Berriche F.
AU - Zeddini B.
AU - Kadima H.
AU - Riviere A.
PY - 2018
SP - 94
EP - 101
DO - 10.5220/0006693200940101