I confess to being a little anxious about organising this event (“Data analytics for learning – beyond learning data”), but thanks to an active, inquisitive and talkative group, I think it was a rewarding hour. My anxiety was rooted in not wanting to have a conversation about learning analytics, with a largely L&D audience, and yet gather people around the theme of data in the industry. The worry was misplaced as there were many shared views I believe.
We covered a fair amount of ground in an hour, even if only with a light touch. This is a summary of my thoughts and reflections from the conversation. I am interested to know what others think.
- “Data is for decision-making” : the purpose of gathering and using data should be to help us take decisions as designers, content developers, instructors, business owners, product managers and such. Reporting on what happened is a narrow slice of what we should be doing.
- Traditional learning data (completions, time spent, attendances etc.) are crude tools for decision-making and are poor indicators of performance change.
- So…why do these measure remain so dominant in L&D? Well, they are simple and easy to gather (familiar and comfortable). It is often what stakeholders and customers expect and ask for, too. We need to raise our sights and those we work with, and press for a more useful set of evidence.
- The history of digital products and tools is built on deep data foundations. L&D needs to dig harder and deeper to have secure and reliable foundations in this respect. Hard but necessary work.
- Thinking about users as consumers can be a very helpful in seeking more useful data and data sources. What is motivating to them? What are they expecting? What behaviours are already familiar? And so on… Evidence that describes people in these ways is often more insightful.
- Moving beyond learning data will require significant changes for many. New relationships in our organisations and fresh requests to those new contacts are needed to access business and commercial data. Influencing suppliers and partners to supply more sophisticated data sets will also be needed. From the conversation, there is a sense that this will take many beyond their comfort zone.
- Making these changes to move beyond learning data is hard work. It takes time and consistent effort, as all valuable things do. But such is our task: to create the evidence based foundations and focus on the real value beyond production and delivery.
- There seems to be low confidence and a reasonable level of anxiety in L&D about tackling data and analytics. Maybe the root of this is the significant change it represents to what we work on, who with and how we go about it?
As I say, this is my brief summary from the conversation. It was a properly fascinating discussion and one to which we may well return…