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Towards a Multi-stage Strategy to Teach Enterprise Modelling

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 334))

Abstract

This paper is concerned with the teaching of enterprise modelling. Enterprise models play an increasingly important role in society. In general, such models are not created as mere “one off” artefacts. They rather have a life of their own, covering a broad range of uses (from analysis and understanding, via simulation and design, to execution and monitoring), while involving an even broader variety of stakeholders/audiences. In our view, this increased use of, and even increased dependence on, enterprise models, also makes it important to teach people how to model well.

The aim of this paper is therefore twofold. Firstly, it aims to identify key challenges in teaching enterprise modelling. Secondly, it also aims to provide the humble beginnings of a multi-stage strategy to teach enterprise modelling, meeting these challenges. Both are rooted on a theoretical perspective of modelling, as well as practical experiences. We also reflect on the need for future experimentation and theoretical underpinning of the suggested teaching strategy.

This work has been partially sponsored by the Fonds National de la Recherche Luxembourg (www.fnr.lu), via the ValCoLa and CoBALab projects.

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Notes

  1. 1.

    All authors have, next to their work in research, also worked in industry, doing different assignments involving modelling, and/or have been teaching conceptual modelling to students and/or practitioners.

  2. 2.

    More colloquially also known as the Sapir-Whorf hypothesis.

  3. 3.

    To keep the diagram clean, we have omitted all of the so-called reference schemes, which identify how e.g. a Doctor or a Patient is referred to in this domain.

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Proper, H.A., Bjeković, M., van Gils, B., Hoppenbrouwers, S.J.B.A. (2019). Towards a Multi-stage Strategy to Teach Enterprise Modelling. In: Aveiro, D., Guizzardi, G., Guerreiro, S., Guédria, W. (eds) Advances in Enterprise Engineering XII. EEWC 2018. Lecture Notes in Business Information Processing, vol 334. Springer, Cham. https://doi.org/10.1007/978-3-030-06097-8_12

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