Within the Intelligent Campus project we have been reflecting on the data sources that we would need to extract data from in order to undertake relevant analytics and also display on a future dashboard.
When it comes to the physical campus and estate there are similar kinds of data that can be gathered about the physical estate itself, but also how people (students and staff) move around that estate.
The following are potential data sources from the estate:
Learning space description
Movement and tracking data
The following are additional non-physical potential data sources:
Student Records (MIS or SIS)
Progress checker (eg Promonitor)
Some of these may be in the same system, but what is important is understanding how to extract data from these systems in a format that can then be stored in the Learning Data Hub (the new name for the Learning Records Warehouse).
Considering we can define the requirements on how this data should be structured, then it won’t matter which systems are used, the data can be extracted and added to the Learning Data Hub. In some cases standards already exist, which we will use.
Some of this data will be static, or generally static, whilst other data sets will be constantly changing and updating on a regular and irregular basis. That will also define how the data is entered into the system. For example mapping data is static (it changes very infrequently) whereas tracking data is dynamic and changing all the time.
Once the data is in the hub then we can start to analyse the data and see what we can learn and see how we can improve the student experience and see what efficiencies can be gained from more effective use of the estate.
Of course there are ethical and legal issues that need to be considered and taken into account, as well as ensuring consent from the learners and staff who may be tracked.