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Providing personalized e-learning environment is normally relying on a domain model representing the knowledge to be acquired by learners and learners’ characteristics to be used in the personalization process. Therefore, constructing the domain model and understanding the characteristics of the learners are very crucial in such an environment. With the inclusion of social collaboration tools for collaborative learning activities, the generated data during conversations enrich with valuable information to be used for personalization. However, when considering chat conversations as a source for constructing the domain model, there is a need to perform a mining technique for chat conversations in order to extract the semantic relations from the user-generated contents hidden inside these conversations. As well as the learner’s characteristics like learning style and knowledge level expressed during conversations. Thus in this paper, we are aiming for the best utilization of chat conversation by proposing a model containing a rule-based technique as a form of mining technique. This mining aims at extracting the semantic relations to build the domain model as an ontology-based depiction. In addition, the mining model is proposed to perform some collaborative filtering techniques to identify the learning styles and knowledge level of the learners.

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Abstract:Collaborative e-learning has a set of characteristics which requires interaction and negotiation among learners and teachers. It also needs support to achieve high-level requirements for learning content and systems such as accessibility, reusability, interoperability and adaptability. The focus of this paper is to investigate three commonly used standards in e-learning which are: SCORM, IMS-LD, IEEE and LOM to enhance the characteristics of collaborative e-learning in relation to the features of these standards. Due the lack of collaboration features in these standards, this paper highlights Service-Oriented Architecture (SOA) features to fulfill the collaborative e-learning requirements.