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Tech Report kmi-97-11 Abstract


The Virtual Participant: Lessons to be Learned from a Case-Based Tutor's Assistant
Techreport ID: kmi-97-11
Date: 1997
Author(s): Simon Masterton
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We describe a system which uses an agent-based approach to support teaching in the collaborative setting of asynchronous plain-text electronic conferencing. We have identified areas within which tutors who use conferencing need support and developed a system which helps out in an opportunistic manner. The agent we have developed uses a case-based approach to instruction by offering help on common student problems. The cases used are examples of problems experienced by students in previous years and discussions of how they were resolved. These cases are presented by the agent when it identifies an appropriate point in the conference. An experimental version of this agent, which we call the 'Virtual Participant' (VP), has been tested on the Open University MBA course 'Creative Management'. We review the effect of the system and the lessons to be learned from this experiment.

Publication(s):

Accepted at CSCL'97
 
KMi Publications
 

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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