The intelligent learning systems provide a direct customized instruction to the learners without intervention of human tutor on the base of Semantic Web resources. The principal role ontologies play in these systems is as an instrument for modeling learning process, learner, learning objects, and resources. In the chapter, a variety of relationships and conceptualizations of ontologies used in the intelligent learning systems are investigated. The utilization of domain and application ontologies in learning object building and knowledge acquisition is represented. The conceptualization of domain ontologies in e-learning is presented by the upper levels of its taxonomies. Moreover, a method and an algorithm intended for generation of application ontologies of structural learning objects (curriculum, syllabus, topic plan, etc.) are developed. Examples of curriculum and syllabus application ontologies are given. Further these application ontologies are used for structural learning object generation.
TopIntroduction
Primarily, an intelligent learning system (ILS) (called also intelligent tutoring system, ITS) is fully adaptive (personalized) e-learning system without human teacher participation. The adaptive e-learning is agent-based, learner-oriented and its best implementation through the resources of the Semantic Web could be achieved. By Stojanovic, Staab, and Studer (2001, p.1177):
In fact, the Semantic Web could be treated as a very suitable platform for the implementation of an e-learning system, because it provides all resources for (e-learning) ontology development, ontology-based annotation of learning materials, their composition in learning courses and the (pro)active delivery of the learning materials through e-learning portals.
A general schema of ILS representing the modules and the participants in ILS activities on Figure 1 is given. The ontology engineer builds and supports ontologies necessary for e-learning activities by an application named ontology editor. The author creates and supports learning content (courseware) according to own learning strategy and using authoring system editor and ontologies. In many cases one might say that “the courseware is constructed by the author simply by identifying the sequence of learning objects references which participate in the courseware” (Atif, Benlamri, & Berri, 2003, p.65). The annotated by metadata and reusable learning objects1 (LO) are archived in a learning content repository (or LO repository) that is a kind of digital library.
Figure 1. General schema of intelligent learning system
By our investigation (Deliyska, & Manoilov, 2009, p.310) the characteristics of ontology-based e-learning determine necessity of following software agents:
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Pedagogical agent (facilitator or course instructor) helping learning process by determining individual learner path in LO chain according to the author learning strategy;
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Content agent (content selector or LO supplying agent) searching and extracting LOs from the repository and supplying them to the learner;
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Input agent checking learner account and actual learner status in the beginning of each learning session, and;
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Assessment agent evaluating test results and registering them in the learner model database.
Generally, agents are servlets or server-based scripts embedded in user interface. The relationships between ILS agents and ontologies in (Deliyska, & Manoilov, 2009, p.313) are examined in more details.
The learner model is formal description of profile, knowledge and behavior of learner and contains data about personalization (individualization) and the adaptability of the e-learning in an online learner-centered environment. The learner receives LO by its own interface (personal e-learning portal or personal learning space) proposing various services – LO searching, delivering and visualization, browsing some entry level content materials (course syllabus, LO examples etc.) directly from the learning content repository, communication with other participants in e-learning process etc.
Within ILS the ontologies are used at two main stages – at the time of courseware building and in the process of knowledge acquisition (learning session).
Generally, ILS is a distributed system whose modules can be independent and located in different nodes (servers) on the Web.
This work is an extension and improvement of (Deliyska, & Manoilov, 2010) and its goal is to define the ontologies used in ILS including its conceptualization.
Firstly, we formulate and examine ILS ontologies and their relationships. Further the conceptualization schemas of the of e-learning domain ontologies are given. A method and an algorithm of conceptualization of application LO ontologies are drawn. In the end conclusions and future work considerations are discussed.