Alke Martens

Autonomous Semantic Structuring of Lecture Topics - Synthesis of Knowledge Models.

Students attending lectures in universities suffer from a weak structural awareness on lecture content. According to learning theories, structural awareness is a relevant factor to association and comprehension of new learning inputs. We synthesize semantic structures from non annotated lecture slides using Topic Modeling algorithms to identify relevant terms and relate them in force-directed graphs. The synthesized graphs provide a structural overview on the topic distribution and relations of non annotated sequential lecture slides.

SYNTHESIS OF PEDAGOGICAL ANNOTATIONS

For the creation of learning session in an ITS pedagogical knowledge is needed. This is created by teachers. An ITS (Intelligent Tutoring System) should have some abilities of teachers, e.g. for learning content creation. It is the future of ITSs to be more independent from human pre-defined content. This would allow an ITS to reduce the workload of teachers in adapting content to a student through automatic creation of learning content. This paper introduces a concept of different layers of information to be used with a rule system with which annotations in an educational context for expert knowledge can be created. The level of automation is one step beyond the classical ITS concept.