in web-based e-learning environment every learner has a distinct background, learning style and a specific goal when searching for learning material on the web. The goal of personalization is to tailor search results to a particular user based on that user's contextual information. The effectiveness of accessing learning material involves two important challenges: identifying the user context and modeling the user context as ontological profiles. This work describes the ontology-based framework for context-aware adaptive learning system, with detailed discussions on the categorization contextual information and modeling along with the use of ontology to explicitly specify learner context in an e-learning environment. Finally we conclude by showing the applicability of the proposed ontology with appropriate architectural overview of e-learning system.
Abstract-During the recent years, the semantic technology such as ontology based representation of metadata has influenced the research, in the area of educational software for accessing, searching and structuring of e-learning contents to provide personalized, adaptive and context aware delivery of learning content. In this paper, we present ontology-based resource description metadata model which is particularly useful for context-aware adaptive e-learning situation. First, we mentioned some of the features to be considered in developing resource description ontology then proposed an ontology called Context-aware Adaptive Learning Resource Ontology (CALRO) that is suitable for delivery of content according to learner contextual information such as learner's learning style and characteristics of the learning device. Finally, we discuss the concerned adaptation approach and its workflow behavior.
Learners who use educational applications need to get suitable learning material in their concerned domain. However, their level of knowledge, preferences and interests are different. The e-learning system should be able to deliver suitable learning materials based on learner's preferences and knowledge. The solution is knowledge based personalized model-driven approach. The learner-model and domain-model plays an important role for delivering personalized learning material to learner. In this paper we proposed an ontological representation of learner-model with domain and educative support preferences along with this we described various categories of information that needs to be considered while developing the domain ontology for managing e-learning material. Finally the concerned architectural overview of ontology based e-learning system is proposed.
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