Without data, no learning analytics. Data sharing is a precondition for even thinking about the benefits of personalised learning, improved retention, better learning design, and all the other promises of learning analytics. To make data sharing happen, we need to understand the barriers and enablers. This is the aim of a small survey the LACE project is carrying out to prepare a deliverable on Data Sharing Requirements and Roadmap.
We would like your input. Please join us in a brainstorming activity, first coming up with issues and concerns that could be seen as enablers and barriers to data sharing. Go to this URL bit.ly/lashare (and share the link with your networks)!
You will be taken to a form with the following introduction and prompt:
Data sharing can be defined as the release of data for use by others. Data sharing may involve deposit, sharing, reuse, curation and preservation of data. There are both barriers and enablers to data sharing. This is your focus prompt, which is the basis for the brainstorming activity:
FOCUS PROMPT: In particular, one issue that should be considered in relation to data sharing for learning analytics is …
… then you add your ideas. Please give us a couple of minutes of your time!
If you have questions, please don’t hesitate to contact us!
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