Automated Course Composition and Recommendation based on a Learner Intention

Traditionally, the presentation order of the learning objects in a course must be described previously and manually. In a personalized tutoring system that may give different courses to different learners, planning the presentation order of courses can be irritating and time-wasting. This paper proposes an approach that can automatically composite and recommend courses to learners with different presentation order and in accord with their intentions. First, a course MAP is constructed according to the contents of related domain ontology and Web pages collected form the Internet. Then, a learner's intention is analyzed for compositing automatically suitable orders of the learning objects to form a personalized course. This proposed approach can also recommend learning objects according to a learner's preferences and others' feedbacks. By this approach, personalized courses can be achieved more easily.

[1]  Ming-Che Lee,et al.  An Ontological Approach for Semantic-Aware Learning Object Retrieval , 2006 .

[2]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[3]  Keqing He,et al.  Towards Representing FCA-based Ontologies in Semantic Web Rule Language , 2006, The Sixth IEEE International Conference on Computer and Information Technology (CIT'06).

[4]  Tzone-I Wang,et al.  Java learning object ontology , 2005, Fifth IEEE International Conference on Advanced Learning Technologies (ICALT'05).

[5]  Kun Hua Tsai,et al.  A Learning Objects Recommendation Model based on the Preference and Ontological Approaches , 2006, Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06).

[6]  Kun Hua Tsai,et al.  A Service-Based Framework for Personalized Learning Objects Retrieval and Recommendation , 2006, ICWL.