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  4. Best-of-Breed: Service-Oriented Integration of Artificial Intelligence in Interoperable Educational Ecosystems
 
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2023
Conference Paper
Title

Best-of-Breed: Service-Oriented Integration of Artificial Intelligence in Interoperable Educational Ecosystems

Abstract
Artificial Intelligence (AI) offers great potential for optimizing learning processes, teaching methods, learning content, or organizational procedures. However, the success of AI components in educational environments is by no means guaranteed and depends on several conditions in their respective learning settings. In this article, we analyze requirements that are often addressed prior to introducing AI features. We address organizational, methodological, didactical, content-related, and technical challenges. The research question of this work is how AI features can best be incorporated into modern educational system landscapes to create sustainable system architectures that are accepted and perceived as added value by users. Thereby, the article discusses two approaches to software architecture: Best-of-Suite (for monolithic architectures) and Best-of-Breed (for service-oriented architectures). Monolithic systems offer a wide range of functions, can be offered by a single provider but can become difficult to manage and create dependencies. Specialized and service-oriented systems, in turn, consist of modular functions handled by specialized services, are more flexible and scalable, and can be integrated with a wide range of tools and services, but require more effort to set up and manage. We explain why the Best-of-Breed strategy is a sensible approach to the use of AI components, how this can be implemented sustainably with the help of a middleware component, and we report on the user experiences from a field test. While in this work we evaluate the implemented system with a cybersecurity training as an on-the-job course, the middleware has been successfully used in other educational contexts, as well.
Author(s)
Krauss, Christopher  orcid-logo
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Streicher, Alexander  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Poxleitner, Eva  
Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. ZV  
Altun, Daniela  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Müller, Joanna
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
An, Truong-Sinh  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Müller, Christoph
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Mainwork
Learning Technology for Education Challenges. 11th International Workshop, LTEC 2023. Proceedings  
Conference
International Workshop on Learning Technology for Education Challenges 2023  
Open Access
File(s)
Download (421.01 KB)
Rights
CC BY-SA 4.0: Creative Commons Attribution-ShareAlike
DOI
10.1007/978-3-031-34754-2_22
10.24406/h-443063
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. ZV  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Keyword(s)
  • Artificial Intelligence

  • Best-of-Breed

  • Learning Analytics

  • Didactic

  • Interoperability

  • Middleware

  • Best Practice

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