What is Learning Analytics?

Our research department is currently housing a student from a different instition who is interested in mobile learning. She has just finished her doctorate in a Spanish university and is about to head home to China. During a welcome meeting our guest proclaimed an interested in mobile learning and Learning Qnalytics. One of our departments professors then singled me out, “David knows all about Learning Analytics”.

I really should know about Learning Analytics. I’m currently involved in a EU project with the term Learning Analytics in the title. I helped write a paper on tools for learning analytics and have read many papers coming out of our department on it.

The student looked at me, raised an eyebrow. I waved my hand, said that we can catch up later, worried that I still don’t haven’t a clue about Learning Analytics. I just don’t have an answer to the question: ‘what is Learning Analytics?’. I can’t claim that data informed decision-making is a new thing, I don’t suppose it’s even new in the context of applying it to education. Also, how does it differ to educational data mining? I’ve never really understood that; I read somewhere that education data mining included academic analytics in it’s scope, I guess because academics aren’t learning anything they can’t be included in learning analytics, who knows.

The trouble is that when it comes to Learning Analytics I don’t think there is a good snappy sound bite on learning analytics to spurt out when your professor drops you in it at the meeting. Fortunatly there a list of 5 things in a Cetis briefing paper by my colleagues that I always return too whenever I am lost in learning analytics. These 5 areas of learning analytics are

1. For individual learners to reflect on their achievements and patterns of behaviour in relation to others.
2. As predictors of students requiring extra support and attention;
3. To help teachers and support staff plan supporting interventions with individuals and groups.
4. For functional groups such as course team seeking to improve current courses or develop new curriculum offerings.
5. For institutional administrators taking decisions on matters such as marketing and recruitment or efficiency and effectiveness measures.

This isn’t a snappy sound bite but I think it does a good job describing what is trying to be achieved. I particularly like that when you think about them, the aims are actually at odds with each other. The needs of individual learners and the needs of institutional administrators conflict, I wonder how many University’s could honestly say that their marketing campaigns have the students best interests to heart.
While the two things that often come up when talking about Learning Analytics  are  1) data mining on 2) educational data the list of 5 areas makes me think that another core ‘thing’ to data analytics is 3) managing conflict of interests.

The list mentions 5 groups that will benefit from using data in the decision-making process, but the list does not include groups that will benefit from data being created. Somebody inside the educational domain may generate the data but the organisation hosting the data is not, and the generator will be influenced by the hoster. I recently saw a tweet proclaiming that Twitter was the authors favourite continued professional development tool. I totally get what they are saying; while Twitter is not a tool of choice for me I think that Reddit and Youtube are tools for my lifelong learning. But Twitter, Reddit, Youtube all have business models built around the generation of data. Infact the only time I use Twitter is for self promation, so I clearly have an agenda there and Youtube users are currently being told how they should create content (so that it makes the most money for Google).

So while a case for using social media data in Learning Analytics is evident, the generators of data have been strongly pushed to use such the tools in a certain way to generate a certain type of data. Its hard not to notice the effort placed by Google in guiding content creators in to creating the types of channels and videos that will generate them the most money. While it isn’t Learning Analytics to use the data in Twitter to gain an insight in to actionable actions that will help Twitter rise it’s stock; the service will certainly will try and get you to create data that does just that.

I think the 5 areas are the best way to describe what Learning Analytics does to somebody because it skips over the ‘… wells there’s some data mining going on …’ bit and says there are a lot of groups of people in education who want to use data for different aims and those aims can cause tension against each other. I’m sure the identified groups have different ideas on what is best for education too! At the heart of all this is really hard questions around who created the dataset, what was it intended for, how were they influenced and what are the implications are when it is used in a certain context.