Abstract:

Many students often need additional resources or tools during learning. Finding and using additional tools or content is important for achieving higher results. Learning in the cloud proposes a grand amount of various sources from useful software tools to interesting and useful additional learning content, or access to some related courses. It is important to support learners in his attempts to find easily the needed content or tools at every moment. This can be done by integrating an efficient and friendly intelligent searching and recommendation system as a part of the e-learning environment. Appropriate semantic description of available resources and intelligent software tools to support the learner in the resource searching and selection process becomes more and more useful for supporting learning activities in the Cloud environment. In this research we analyze new possibilities that cloud technologies propose to enhance e-learning and give possibilities for learners to manage its own learning. We will discuss the role of the Cloud for storing incremental e-learning content and computational resources for using learning analytics. We will explore the impact of combination of ontological knowledge models and cloud computing (including cloud services or intelligent agents) on modern e-learning.
We propose an ontology-based knowledge model of tutoring domains, and a conceptual model of a recommender system for supporting learners in the process of searching learning resources and cloud-based tools or widgets. Our knowledge model consists of mapped domain ontologies of two main types: lightweight general taxonomies and small precise knowledge models (ontologies) of learning objects or resources, including complete definitions and relations between learned concepts. We will align precise domain ontologies and general taxonomies by semantic relations (such as “defined in”, “prerequisite”, “explained in”, etc. ). We also use mappings between learning domain, learning goals or learner profile ontologies. This is very important for supporting learners in finding learning resources or cloud services.
The proposed conceptual model of the recommender system is agent-based. It includes an interface agent, a searching agent, an ontology mapping agent, a learning resource annotation agent, a coordinator agent, and a textual resource analysis and comparison agent. The main purpose of the system is to search and recommend learning resources. It compares resources, searchs and recommends cloud-based tools, widgets or services, useful in the learning process. We will discuss the usage of the ontology and agent-based recommender system as a complement of an adaptive knowledge-based educational system for personalized learning.

Keywords:

Intelligent educational system, personalization, ontology, E-learning, cloud-based services