Towards an Ontological Infrastructure for Content Modeling and Personalization

Content modeling allied to personalization features improves both the design/reuse of learning materials and student learning. Nevertheless, content modeling and personalization are often studied separately as different research topics. To address this problem this paper describes the creation of an ontological infrastructure, OntoToLearner, which integrates a content modeling approach, referred to as IMA-CID, with domain and user models in order to personalize a content presentation. OntoToLearner uses student´s preferences and background together with the conceptual and instructional models of IMA-CID to change the levels of granularity when presenting a content. To combine content modeling and personalization we formalized the concepts and relationships of IMA-CID and connected them with three other ontologies (navigation ontology, domain ontology and user model ontology). As a proof-of-concepts we generated and instantiated different types of users (e.g. novices and experts students) and developed a domain ontology for Function Point Analysis. We also created rules that use OntoToLearner´s infrastructure to automatically select, build and present the content to students. The results suggest that our approach can take the students´ characteristics as an input to model the content using the IMA-CID approach, and thus, create more personalized and well-structured learning materials.