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Learning Management Systems (LMS), as the most widely used online learning systems in formal education, confront all learners with the same learning environment, although the learning-relevant characteristics of the learner are by no means homogeneous. In this article, we highlight ways in which LMSs, by linking institutional data sources and analytics tools, can provide personalized learning environments that adaptivly adjust to learners' needs and learning progress. In future adaptive personalized learning environments, the LMS as we know it today will merely be a building block within an open, modular, and distributed system architecture. We propose a five layer architecture that fits into the existing IT landscape of educational institutions and enables the coexistence of different components and paths for processing, storing, and analyzing data for the adaptation of personalized learning environments. The components in each layers can be complemented or replaced by other systems and services as long as the interfaces of the neighboring layers can still be served. This allows not only a step-by-step construction of a complex system landscape, but also a distribution of the computing load and multiple use of resources and services. |
