Learning Analytics Classroom Hacks: Examples from a Australian University

Roger Dawkins gives an interesting insight in the use of Learning Analytics in three blended learning undergraduate courses in Academia, Companion Proceedings 8th International Conference on Learning Analytics & Knowledge (LAK18)). His purpose is to find an answer for the question: ‘are my undergraduate students reading my (blended) unit’s online content. More specifically, ‘what is the Click through rate (CTR) of my content. With this data could help him to make educated decisions about changes to content and improvements in his blended learning course.

Various obstacles and Learning Analytics Hacks
e described clearly the various obstacles in his learning analytic activities. Even more interesting is that he decided to prepare Learning Analytics Hacks in order to be able to collect the data about CTR. This was necessary because the Course Analytic data possibilities of the LMS used in his university (Blackboard) were not sufficient to collect the necessary data.

He considers the evaluation of the hacks as a very complex process. To unpack this complexity he uses the perspective of orchestration: ‘Orchestration understands that student activity and learning involve multiple stakeholders and a variety of technologies distributed across different spaces.

Some issues
These hacks enabled him to make data-driven iterative changes to unit design/content. And in addition, student surveys show an increase in satisfaction with the resources of one of the courses. Also, he identifies several issues:

  • Some limitations of the learning management system used in his university;
  • The need for multiple metrics and benchmarks for a context-rich understanding of engagement and effective iteration. As a result, he considers, the optimization of the content of his courses was largely guesswork;
  • The difficulty of avoiding university (technical) support for small-scale learning analytic initiatives;
  • The importance of recognizing that ethical grey areas can appear without being anticipated (and be overlooked);
  • The need to accept that some teachers could be ignorant of their university’s broader learning analytic initiatives and how this might relate to their own classroom-based teaching goals;
  • The importance (and difficulty) of gathering learning analytic data unobtrusively.
Learning Analytics Classroom Hacks: Examples from an Autralian University