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People | Member | Simon Buckingham Shum

Professor of Learning Informatics

My work is inspired by the vision and >40 years’ work of pioneer Doug Engelbart: to develop technologies which “augment human intellect”, our “collective capability for coping with complex, urgent problems.”

My current work revolves around these separate but also intersecting fields:

* Collective Intelligence infrastructure (technologies and ways of working that pool what is known) for contested knowledge (these days most claims are contestable, and in any serious dilemmas, there is disagreement about the way forward).

* Learning Analytics (how do you know if someone is learning from the digital traces they leave behind?), in particular, for 21st century qualities (the personal skills and dispositions that citizens need to thrive in an age of turbulence and complexity — starting at primary school).

Keys: Learning Analytics, Collective Intelligence, Argument Visualization

Projects
Election Debate Visualization
Catalyst
SocialLearn
View all 18 Projects

Technologies
Evidence Hub
Cohere
D3Eprints
View all 7 Technologies


5 Most Recent External Publications

Publications | Visit External Site for Details Publications | doi

Simsek, D., Buckingham Shum, S., De Liddo, A., Ferguson, R. and Sándor, Á. (2014) Visual Analytics of Academic Writing, Demo at The 4th International Learning Analytics and Knowledge, Indianapolis, IN, USA, pp. 265-266, ACM New York, NY, USA ©2014

Publications | Visit External Site for Details

Knight, S., Buckingham Shum, S. and Littleton, K. (2014) Epistemology, assessment, pedagogy: where learning meets analytics in the middle space, Journal of Learning Analytics, UTS ePress

Publications | Visit External Site for Details

Knight, S., Arastoopour, G., Shaffer, D., Buckingham Shum, S. and Littleton, K. (2014) Epistemic networks for epistemic commitments, International Conference of the Learning Sciences (ICLS), Boulder, Colarado, USA

Publications | Visit External Site for Details

De Liddo, A. and Buckingham Shum, S. (2013) Improving Online Deliberation with Argument Network Visualization, Workshop: Digital Cities 8 at 6th International Conference on Communities and Technologies, C&T 2013, Munich, Germany

Publications | Visit External Site for Details

De Liddo, A. and Buckingham Shum, S. (2013) The Evidence Hub: Harnessing the Collective Intelligence of Communities to Build Evidence-Based Knowledge, Workshop: Large Scale Ideation and Deliberation at 6th International Conference on Communities and Technologies, Munich, Germany

View all 117 publications

5 Most Recent Tech Reports


Epistemic Networks for Epistemic Commitments
Techreport ID: kmi-13-03
Date: 2013
Author(s): Simon Knight, Golnaz Arastoopour, David Williamson Shaffer, Simon Buckingham Shum, Karen Littleton
View Abstract Web Version


Social Learning Analytics
Techreport ID: kmi-11-01
Date: 2011
Author(s): Simon Buckingham Shum,Rebecca Ferguson
View Abstract Download PDF


Designing the Ontological Foundations for Knowledge Domain Analysis Technology: An Interim Report
Techreport ID: kmi-08-02
Date: 2008
Author(s): Neil Benn, Simon Buckingham Shum, John Domingue, Clara Mancini
View Abstract Download PDF


Visualising Discourse Coherence in Non-Linear Documents
Techreport ID: KMI-06-19
Date: 2006
Author(s): Clara Mancini, Donia Scott and Simon Buckingham Shum
View Abstract Download PDF


Sensemaking on the Pragmatic Web: A Hypermedia Discourse Perspective
Techreport ID: KMI-06-16
Date: 2006
Author(s): Simon Buckingham Shum
View Abstract Download PDF

View all 44 Tech Reports  

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Knowledge Media Institute | The Open University | Brian Buckingham Shum

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KMi 2013 - A review of the year

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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.

Visit the MMIS website