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olnet project full details

Champion: Simon Buckingham Shum
Professor of Learning Informatics RDF Icon
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Participant(s):Michelle Bachler, Anna De Liddo

Similar Projects:Cohere, OpenLearn

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OLnet

Open Learning Network

The aim of OLnet is to tackle gathering evidence and methods about how we can research and understand ways to learn in a more open world, particularly linked to Open Educational Resources (OER) but also looking at other influences. We want to gather evidence together but also spot the ideas that people see emerging from the opportunities.

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Publications

Publications | Visit External Site for Details Publications | doi 
Publications | Visit External Site for Details  

De Liddo, A., Buckingham Shum, S., McAndrew, P. and Farrow, R. (2012) The Open Education Evidence Hub: A Collective Intelligence Tool for Evidence Based Policy, Cambridge 2012: Joint OER12 and OpenCourseWare Consortium Global 2012 Conference, Cambridge, UK

Publications | Visit External Site for Details Publications | Visit External Site for Details  

Okada, A. (2011) COLEARN 2.0: Refletindo sobre o conceito de COAPRENDIZAGEM via REAs na Web 2.0, in eds. DANIELA BARROS CLAUDIA NEVES FILIPA SEABRA JOSE MOREIRA SUSANA HENRIQUES, Educacao e tecnologķas: reflexao, inovacao e praticas, 1, 978-989-20-2329-8, pp. 18, Lisbon: Universidade Aberta de Portugal

Publications | Visit External Site for Details  

Buckingham Shum, S., Cannavacciuolo, L., De Liddo, A., Iandoli, L. and Quinto, I. (2011) Using Social network Analysis to Support Collective Decision-Making Process, International Journal of Decision Support System Technology, 3, 2, pp. 15-31, IGI Global

Publications | Visit External Site for Details Publications | Visit External Site for Details  

De Liddo, A. and Panagiota, A. (2010) A Method and Tool to Support the Analysis and Enhance the Understanding of Peer-to-Peer Learning Experiences, OpenED2010: Seventh Annual Open Education Conference, Barcelona, Spain

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Research Themes

Latest Seminar
Microsoft Research Cambridge

Actions and their Consequences: Implicit Interactions with Machine Learned Knowledge Bases

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