< Digital Learning Environment

Introduction Learner Analytics and Learner Support

Digitization of learning environment can not only refer to the digitization of learning content, but also to the digital "sensors" in a learning environment for collecting data from a learning process. The presence of sensors in the learning environment allows the use of methods from the area of "Learning Analytics"[1] section. The generic approaches can be introduced at a specific geolocation and adapted to other geolocations. On the one hand, the content-related developments and the educational design of different levels of support of learners can be developed and on the one other hand the OER principles allow the collaboratively adaptation of the content to other languages, different skills of learners and other locations, for which the learning resources refer to.

Learning Tasks

  • (Standards) Explore existing standards, that can be used for learner analytics?
  • (Privacy Friendlyness) Explain the benefits of generic concepts that can be used in different learning environments and in which each learner could use their own learner profile in a privacy-friendly way. Profile is used to tailor the learning environment according to different requirements and constraints.
  • (BarCode) Explain how Barcodes can be used for Learner Analytics and individualized support in a digital learning environments.
  • (Mobile Devices) Explore the differences between LineageOS and a commercial Android operating system. What would be necessary to install LineageOS on mobile devices so that the learner analytics data is accessible in the educational unit (classroom, school, university, ...) only. Root access to a mobile device is general the ability to control all the installed and available software on a device. Root access provides control over the device which is especially required to have full control over the network active components of the Operating System and the learning environment. Identify the obstables to using LineageOS in a privacy friendly digital learning environment that applied learner analytics.


See also

References

  1. ↑ Siemens, G., & d Baker, R. S. (2012, April). Learning analytics and educational data mining: towards communication and collaboration. In Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 252-254). ACM.
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