The Tele-TASK Personal Lecture Butler project of the team of Prof. Dr. Christopp Meinel aims at providing personalized e-learning based on the dynamic composition of lectures subparts. The solution proposes a personalized lecture to a learner according to its needs and according to its current knowledge about the subject. Our solution is particularly interesting for education in a self-directed learning environment, where it fosters autonomous and exploratory learning.
The preparation work for the Tele-TASK Personal Lecture Butler included among others the splitting of the lecture videos of about 90 minutes duration each into useful sections of 5 to 20 minutes covering single topics. The sequence answering the user's question is then covered by a sequence of those small sections, also called Learning Objects as defined in the Learning Object Model. That way, the Personal Lecture Butler discards videos from the sequence which are already known to the user or not required to understand rest of the answer. Thus, the Personal Lecture Butler contributes to an efficient and convenient e-learning platform.
Different technologies from the Sematic Web are used to perform this task, comprising the semantic annotation of the lectures and the development of a domain ontology. The dependencies between the different learning objects are partially derived from that ontology. Besides that, dependencies can also be entered manually or be derived from the table of contents of a lecture series. Using speech recognition and other technologies, the closely related ExSIT project contributes to the ontology on the one hand, and to the automated segmentation of video content on the other.
The Tele-TASK Personal Lecture Butler Team is currently working on the prototype implementation and seeks for integration with the Tele-TASK web platform.
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