A Design Framework for Developing Advanced and Intelligent Learning Ecosystems
The ongoing transformation of education around the world aims at personalized, predictive, participative learning methods, supported by technology. It considers individual socio-economic status, conditions, and dispositions in personal, social, and behavioral contexts. Such a transformation requires the deployment of advanced technologies including artificial intelligence for providing a consistent representation and mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc., as philosophy or cognitive sciences. This paper describes related challenges and solutions related to this transformation of learning ecosystems resulting in a formal reference architecture. This reference architecture provides an architecture-centric and policy-driven framework for designing and managing intelligent learning ecosystems in particular.
Keywords: ML, algorithms, AI, software design, AI audit, evaluation frameworks
