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In Technology Enhanced Learning Environments, models can have three roles:

1. Models as scientific tools: They are used to understand and predict some aspects of learning situations;
    
2. Models as components: models correspond to some teaching or learning aspects. There are part of the environment components;
    
3. Models as design basis: models are representations of some learning processes and serve as a basis for proposed IT tools. In our research work, models fulfill roles 2 and 3 and are based on Knowledge Engineering. It is a matter of explicitly representing knowledge involved during learning processes.

Our research activities focuses on problems related to knowledge acquisition and representation, sensitivity to context, adaptation, and interoperability on the semantic level.

• Ontologies development for knowledge reference models, context models, adaptation models, interaction models, instructional scenarios models, user models in which personal knowledge graphs, extension of personal learning environments.
   
• Reasoning based on previous models to support learning.
   
• Semantic Web and Linked Data in order to ensure interoperability, reutilization, and data sharing but also a context for consulted and produced data, learning activities, traces use, etc.
   
• Collection and analysis of traces interaction between the learners and the system to improve learning, in particular, by adapting and/or personalizing proposed resources, activities, etc. 
   
• Dynamic generation of accompanying dashboard both for the learner and for the teacher.

Thus, we have conceptualized and developed an environment that support learning in the open context of the web, by adopting principles of personal learning environments, allowing interactions in groups and in large numbers. This environment is based on knowledge models, activities, individuals and their contexts. We have developed an environment prototype called SMOOPLE acronym for Semantic, MOOC, Pervasive, and PLE (Personal Learning Environment).