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Model-Based Approach to Automated Provisioning of Collaborative Educational Services

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Computational Science – ICCS 2021 (ICCS 2021)

Abstract

The purpose of the presented work was to ease the creation of new educational environments to be used by consortia of educational institutions. The proposed approach allows teachers to take advantage of technological means and shorten the time it takes to create new remote collaboration environments for their students, even if the teachers are not adept at using cloud services. To achieve that, we decided to leverage the Model Driven Architecture, and provide the teachers with convenient, high-level abstractions, by using which they are able to easily express their needs. The abstract models are used as inputs to an orchestrator, which takes care of provisioning the described services. We claim that such approach both reduces the time of virtual laboratory setup, and provides for more widespread use of cloud-based technologies in day-to-day teaching. The article discusses both the model-driven approach and the results obtained from implementing a working prototype, customized for IT trainings, deployed in the Małopolska Educational Cloud testbed.

The research presented in this paper has been partially supported by the funds of Polish Ministry of Science and Higher Education assigned to AGH University of Science and Technology.

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Notes

  1. 1.

    edX, https://www.edx.org/.

  2. 2.

    Coursera, https://www.coursera.org/.

  3. 3.

    Vocareum, https://www.vocareum.com/.

  4. 4.

    Qwiklabs, https://www.qwiklabs.com/.

  5. 5.

    OpenEdx, https://github.com/edx.

  6. 6.

    EEDS Repository: https://github.com/llopisga/cloud-orchestration.

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Correspondence to Marek Konieczny .

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Gandia, R.L., Zieliński, S., Konieczny, M. (2021). Model-Based Approach to Automated Provisioning of Collaborative Educational Services. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12747. Springer, Cham. https://doi.org/10.1007/978-3-030-77980-1_48

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  • DOI: https://doi.org/10.1007/978-3-030-77980-1_48

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