Numéro |
J3eA
Volume 21, 2022
CETSIS 2021 – Colloque de l’Enseignement des Technologies et des Sciences de l’Information et des Systèmes
|
|
---|---|---|
Numéro d'article | 2004 | |
Nombre de pages | 6 | |
DOI | https://doi.org/10.1051/j3ea/20222004 | |
Publié en ligne | 28 septembre 2022 |
Innovative Engineering Teaching Unit in International Context
1
Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, F-59313 Valenciennes, France
2
Duale Hochschule Baden Württemberg, Jägerstrasse 56, 70174 Stuttgart, Germany
3
Metropolia University of Applied Sciences, Myllypurontie 1, 00920 Helsinki, Finland
4
Heriot-Watt University, Edinburgh, Edinburgh, EH14 4AS, Scotland, United Kingdom
This communication is intended to disseminate the first learnings and outcomes of an Erasmus+ Strategic Partnership project (2018-1-DE1-KA203-00423) realized between Sept. 2018 and Aug. 2021 by 4 European applied sci-ence universities. The InT#Tech (International Transfer of cooperative study programmes in Europe: Scientific expecta-tions, challenges and potentials) project’s aim is the development of an international module for coop-students (appren-tices), focusing on the digital transformation of engineering, i.e. the use of massive electronic data in design, manufactur-ing, mobility and facility management. After comparing the different models of coop-studies and identifying common requirements among the partners, after achieving a first level of cooperation during a Summer School, the most challeng-ing task of the project was to imagine, develop, implement and analyse the execution of an innovative teaching unit, constituted of autonomous and supervised work, individual and team-based tasks in international context, theory and practice, distant and local lectures, academic and industrial inputs, so as to be able to grant ECTS credits to the partici-pating coop-students. The paper includes recommendations to universities willing to implement a similar programme.
Key words: Coop-education / International context / Digital transformation / Massive data
© The authors, published by EDP Sciences 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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