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Tech Report kmi-05-01 Abstract


Heroic failures in disseminating novel e-learning technologies to corporate clients: a case study of interactive webcasting
Techreport ID: kmi-05-01
Date: 2005
Author(s): Peter Scott, Kevin Quick
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In principle, it should be easier to disseminate novel learning concepts based in technology enhanced learning to companies. Unfortunately, many corporations seem to be extremely risk averse, and the challenges inherent in the new models seem to be very hard for them to accept. This paper uses the deployment of interactive webcasting systems to present a series of case studies of dissemination successes and failures. We will suggest that the key to successful deployment is in making critical innovation (and its risk) invisible to the client, whilst matching their expectations with an "appropriate" level of technology. This work has led to a new dissemination portal Prolearn.TV.

Publication(s):

Proceedings of the 4th International Symposium on Information and Communication Technologies, Cape Town, South Africa. Jan 3-6, 2005. ACM Press. ISBN 0-9544145-6-X
 
KMi Publications Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.

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