Moving learning analytics from the research labs to the classrooms and lecture halls requires data sharing. Data are not any longer gathered in controlled settings but have to be combined from different sources within the institution and maybe beyond. This scaling up of learning analytics raises a host of questions on behalf of the data subjects providing requirements for design of new solutions and practices. This paper analyses a corpus of more than 200 questions gathered by a European learning analytics support action and explores how these questions could be used to understand the problem space of data sharing and the solution space to be carved out by research and development within this emerging field of learning technologies. The paper concludes the discussion on data sharing and big data for education is still at an early stage, where conceptual issues dominate and there is a long way to go before one can move towards solving issues of technical development and implementation.
|Title of host publication||Workshop Proceedings of the 23rd International Conference on Computers in Education ICCE 2015|
|Editors||Hiroaki Ogata, Weiqin Chen, Siu Cheng Kong, Feiyue Qiu|
|Place of Publication||Japan|
|Publisher||Asia Pacific Society for Computers in Education (APSCE)|
|Number of pages||10|
|Publication status||Published - 2015|
|Event||International Conference on Computers in Education (ICCE 2015) - Hangzhou China, Hangzhou, China|
Duration: 30 Nov 2015 → 4 Dec 2015
Conference number: 2015 (23rd)
|Conference||International Conference on Computers in Education (ICCE 2015)|
|Period||30/11/15 → 4/12/15|
Tore, H., Mason, J. C., & Chen, W. (2015). Data Sharing for Learning Analytics - Questioning the Risks and Benefits. In H. Ogata, W. Chen, S. C. Kong, & F. Qiu (Eds.), Workshop Proceedings of the 23rd International Conference on Computers in Education ICCE 2015 (1 ed., Vol. 1, pp. 228-237). Asia Pacific Society for Computers in Education (APSCE).