What might the Learning Analytics process look like from my perspective?

The starting point for this post is firstly to admit I’m not technical, and secondly, admit I’m no expert on the nuisances of Learning Analytics. However, I am asked quite regularly about it, and I do try to explain what is required from various perspectives. The question is, do I help? I’m not as effective as I’d like to be 🙂 I feel I need a graphical means of enabling around the people round the table to have a meaningful conversation.

The following is an attempt to visualise conversations I’ve had with colleagues, for people who aren’t immersed in learning analytics. I’d love feedback …

The context of use start a conversation around a feature set an institution use as part of a pilot study. Therefore, I’d talk through a general use case, and start to identify the likely indicators used to identify the degree of student engagement. For instance, in a previous post on this blog, I’ve discussed a use of learning analytics to nudge curriculum design to generate timely, actionable data. A use case might be around retention and the need for enhanced reporting on educational data to action appropriate intervention strategies. The proxies for the level of student engagement could be a combination of educational data: LMS/VLE (formative assessments – quizzes, discussion boards, and login data), SIS (summative assessment record), Lecturer Attendance, and engagement with classroom technologies (clickers).

An indicative feature set for an institution to enable this is visualised below,

Indicative Feature Set- Overview (1)


  • Extract, Transform and Load (ETL) refers to a process in database usage and especially in data warehousing that: Extracts data from homogeneous or heterogeneous data sources. Transforms the data for storing it in proper format or structure for querying and analysis purpose.
  • OLAP is an acronym for Online Analytical Processing. OLAP performs multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling.
  • SIS is student information system
  • LMS / VLE is learning management system / virtual leaning environment

I’d suggest a visualisation approach for lay people is a really useful way to move the conversation between the bigger picture of interlinked determinants, such as culture, people and processes and the required technical infrastructure.

It also provides a framework to drive out the questions which would need answering within a learning analytics pilot. This is through exploring the big picture, and how the individual components function. For instance;

  1. What does Learning Analytics mean within your context?
  2. What are the specific questions you’d like answering?
  3. What are the data points and indicators you need to answer these questions?
  4. Where does that data reside? Where and how would it be best stored?
  5. Who can access the data? What is the reporting process?
  6. Is your current curriculum development model generating consistent, actionable learning data?
  7. What are the most appropriate intervention strategies and work flows?
  8. What are the ethical considerations around this use Learning Analytics?
  9. What changes, if any do you need to consider in Policy and Procedures for this use of Learning Analytics?
  10. What is the required evaluation framework and enhancement cycle for Learning Analytics?

Plus many, many more.  So, what should I add to this to make it work for you?

With Thanks – Image – http://www.hightekknowledge.com/wp-content/uploads/2015/03/cube-.jpg


    • andyoutandabout

      Hi Aaron,

      Thanks – I’ll add it to the data sources – some might say a poor show that I didn’t include it in the first place 🙂

      Best of luck with the LA project ….

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