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Framework for the adaptation of an autonomous academic recommendation system as a service-oriented architecture

Abstract

The adaptation of traditional systems to service-oriented architectures is very frequent, due to the increase in technologies for this type of architecture. This has led to the construction of frameworks or methodologies for adapting computational projects to service-oriented architecture (SOA) technology. In this work, a framework for adaptation to SOA in an educational organization is presented, through a specific case of adaptation of an autonomous recommendation system. The framework has a business model that extracts the specific needs of the organization and that will help to project the service architecture from an administrative perspective for a generation of value. The framework has components that conform to the organizational governance of Information Technology (IT) linked to the control mechanisms managed by any IT government of the organization. Finally, the framework has a self-management process that integrates intelligent mechanisms or paradigms for any autonomous process that manages the SOA. In general, the framework describes a methodological process of four general phases, allowing to identify requirements, design services, develop them, and deploy them in an organization, to be managed through control mechanisms through governance. The framework was tested in the adaptation of an autonomous recommendation system for virtual learning environments (VLE), which has two main processes, the creation of an academic course and the use of the course.

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Acknowledgements

This work has been supported by the project 64366: “Contenidos de aprendizaje inteligentes a través del uso de herramientas de Big Data, Analítica Avanzada e IA” - Ministry of Science - Government of Antioquia - Republic of Colombia.

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Correspondence to Jose Aguilar.

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Monsalve-Pulido, J., Aguilar, J. & Montoya, E. Framework for the adaptation of an autonomous academic recommendation system as a service-oriented architecture. Educ Inf Technol (2022). https://doi.org/10.1007/s10639-022-11172-8

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  • DOI: https://doi.org/10.1007/s10639-022-11172-8

Keywords

  • Academic recommendation systems
  • Autonomous computing
  • Service-oriented architecture