A scheme for extracting information from collaborative social interaction tools for personalized educational environments

Personalized e-learning systems are mainly structured based on two basic models: domain model and user model. When considering personalization in a collaborative environment with user-generated content via Web 2.0 technologies, the task of generating the models is very challenging. This paper presents an approach to extract information related to the domain model and user model for the purpose of personalization. The extraction is using chat conversations using different social media tools during collaborative learning as sources for the text analysis. Text mining technique has been incorporated to clean the collected data and extract the required information.