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The Third ACM Conference on Learning at Scale (L@S) invites 
contributions to its Work in Progress and Demonstration tracks.

Deadline for both tracks is January 15th, 11:59pm PST. Please see the 
website for formatting guidelines:

The Work-in-Progress (WiP) track showcases recent findings or other 
types of innovative or thought-provoking work. Accepted WiP papers will 
be presented in the form of a poster at the session.

The Demonstrations track show aspects of learning at scale in an 
interactive hands-on form. A live demonstration is a great opportunity 
to communicate ideas and concepts in a powerful way that a regular 
presentation cannot.

Learning at Scale is at the intersection of computer science and the 
learning sciences, seeking to improve practice and theories of learning 
at scale. Work presented at Learning at Scale reports on rigorous 
research on methodologies, studies, analyses, tools, or technologies for 
learning at scale. Learning at Scale includes MOOCs, games (including 
massively multiplayer online games), citizen science communities, and 
other types of learning environments which (a) provide learning 
experiences to large number of learners and/or (b) produce detailed, 
high volume data about the learning process.

Please see the website for a list of accepted full papers:

The keynotes in Learning at Scale 2016, which will take place in 
Edinburgh, are Sugata Mitra, Mike Sharples, and Ken Koedinger.

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.

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