Vision of the tele-TASK Project

In the center of the research work of Prof. Dr. Christoph Meinel and his team in the field of Knowledge Engineering and Web University is the tele-TASK project (tele-Teaching Anywhere Solution Kit). It was started more than 15 years ago when we began to research how Internet and web technologies can be used for supporting teaching (> tele-teaching) and learning (> e-learning). Our vision was to design an easy to use mobile system for recording and broadcasting university lectures and presentations over the Internet in order to develop and test on the one hand new tele-teaching and e-learning concepts and on the other hand to innovative portal and navigation techniques.

Demonstration des tele-TASK Systems

Our Research Directions

Over the years tele-TASK turned out to be a very fruitful project which helped us, on one side, to gain valuable experiences and a deeper understanding of e-learning and tele-teaching. On the other side, it inspires us to try our upcoming techniques in the are of Web3.0 - semantic, social, service Web -, and to make them accessible for Web-university (details). 

Some Links to the tele-TASK Portal

Here are some links to the tele-TASK portal which provides meanwhile more than 5.000 recorded telelectures: 

Buy, lease or rent tele-TASK

If you like to record and transmit your presentations over the Internet online and offline you can work with our tele-TASK recording system. Simply buy or rent tele-TASK ... 

The tele-TASK Team

  • Prof. Dr. Christoph Meinel (Head)
  • Dipl-Inf. Matthias Bauer
  • Dipl-Ing. Haojin Yang
  • Franka Grünewald, MSc.
  • Dipl.-Inf. Frank Priester (Technical Support)
  • Former Members: Volker Schillings, Tongbo Chen, Mingchao Ma, Mathias Kutzner, Bert Baumann, Long Wang, Andreas Groß, Maria Siebert, ...

tele-TASK Symposia

Scientific Publication about tele-TASK

Lecture Butler - Teaching Reasonable Lectures from a Lecture Video Archive

Martin Malchow, Matthias Bauer, Christoph Meinel
In Proceedings of the 2015 ACM Annual Conference on SIGUCCS, pages 3-9, 11 2015 ACM.

DOI: 10.1145/2815546.2815557

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.

Keywords:

Teleteaching; Tele-Lecturing; Distance Learning; E-Learning;OCR Search; Semantic Web; In-Memory Database; Lecture Video Archive

BibTeX file

@inproceedings{Martin2015a,
author = { Martin Malchow, Matthias Bauer, Christoph Meinel },
title = { Lecture Butler - Teaching Reasonable Lectures from a Lecture Video Archive },
year = { 2015 },
pages = { 3-9 },
month = { 11 },
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. },
keywords = { Teleteaching; Tele-Lecturing; Distance Learning; E-Learning;OCR Search; Semantic Web; In-Memory Database; Lecture Video Archive },
publisher = { ACM },
booktitle = { Proceedings of the 2015 ACM Annual Conference on SIGUCCS },
isbn = { 978-1-4503-3610-9 },
priority = { 0 }
}

Copyright Notice

last change: Mon, 21 Dec 2015 09:49:03 +0100

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