Lecture Butler: Teaching Reasonable Lectures from a Lecture Video Archive

Abstract

Lecture video archives offer a large variety of lecture recordings in different topics. Naturally, topics are described superficially, easily or detailed in different lectures. Users interested in certain topics have problems finding lectures describing a topic chronology from basic lectures to more detailed difficult lectures. The Lecture Butler is going to automatically offer e-learning students lectures for the topics of interest in chronological playlists. The approach is finding lecture information using title, description, OCR and ASR data. This data is indexed and searched by an in-memory database to fulfill the speed requirements for playlist creation. In the search results lectures are going to be ordered by lecture occurrence in the university semester time schedule or by given lecture level of difficulty. As a result students can automatically create playlists for their topic of interest in sequence of the lecture level. Hence, students are not overstrained by lectures when they start with basic lectures first. Basic lectures provide information to understand more complex lectures. The research shows that an automatic approach by adding the level of difficulty or university semester time table is going to show reasonable playlists to find topics of interest. This solves the main problem students encounter when they try to learn a topic step-by-step using recorded lectures. The approach will support and motivate students using e-learning opportunities.