Towards Adaptation Languages for Adaptive Collaborative Learning Support

Collaborative learning involves interaction between students, whilst adaptive learning traditionally involves individual learning progress. Each of these learning paradigms has its advantages and disadvantages, which are mainly disjunctive. In order to create a more powerful learning experience, in an ideal world, these two paradigms should be integrated, in order to alleviate each others' weaknesses. This would render it possible to allow for the coexistence of collaboration in learning environments, along with adaptation and personalization, but would also enable personalized collaboration, as well as collaborative adaptation in learning. This however requires extensions to the way adaptation, personalization and collaboration are approached today. In this paper we gradually extract patterns and abstract specifications and finally show how such extensions can be applied to an adaptation language for personalized learning, in order to enable collaborative learning support.