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In the educational world, only very limited datasets are publicly available and no agreed quality standards exist on the personalization of learning. The SIG dataTEL aims to address these issues by advancing data driven research to gain verifiable and valid results and to develop a body of knowledge about the personalization of learning.

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dataTEL - EATEL SIG on Data-driven Research and Learning Analytics's blog

New book on TEL Recommender Systems at Springer - Recommender Systems for Learning

March 19, 2012 by Hendrik Drachsler   Comments (0)

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Hi there,
we just finished the draft for a new book that focuses on the last 10 years of research on Recommender Systems for Learning.  It expands the relevant chapter on Recommender Systems in Technology Enhanced Learning (by Manouselis, Drachsler, Vuorikari, Hummer and Koper) that was included in the Recommender Systems Handbook published by Springer (2011), and performs anmore extensive and in depth analysis of the recommender systems currently foundnin relevant literature.
The... Read full post



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2nd call for journal papers on dataTEL “Datasets and Data Supported Learning in Technology-Enhanced Learning”

October 12, 2011 by Hendrik Drachsler   Comments (0)

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just a short reminder for the SI dataTEL at IJTEL. There are only 13 days left for your high-quality contributions.We were able to arrange some funding to disseminate the SI as printed copy at relevant scientific events, maybe that gives you some extra motivation for your papers. Regarding multiple requests please use the following template for your submissions: http://www.inderscience.com/mapper.php?id=64 and here is the call again:************************************************CALL FOR... Read full post



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Existing dataset initiatives: Digging Into Data

June 16, 2010 by Riina Vuorikari   Comments (1)

Authors: vuorikari Abstract:
The idea behind the Digging into Data Challenge is to answer the question "what do you do with a million books?" Or a million pages of newspaper? Or a million photographs of artwork? That is, how does the notion of scale affect humanities and social science research? Now that scholars have access to huge repositories of digitized data -- far more than they could read in a lifetime -- what does that mean for research?
Link: http://www.diggingintodata.org/... Read full post



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