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