The umbrella term “business intelligence” has been widely used for many years to refer to the tools, techniques and concepts of analysing raw data and turning it into useful information which can help users and businesses alike gain important insight.
I have been working in the education technology field for about 10 years now and in the past 7 years have been a strong advocate of using business intelligence in education. It is well known that collecting good data on learner progress and performance is invaluable to supporting those learners. By using business intelligence tools and techniques, such as data analytics, education organisations can use the data they have about learners and their organisation to help drive improvement and support individuals who may be struggling.
However, the term “learning analytics” is relatively new to me, which I came across whilst I was researching a project on student retention analytics.
In his Educause article “Penetrating the Fog: Analytics in Learning and Education” George Siemens has a good definition of learning analytics, and how it differs from “organisational BI”:
“Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs. Academic analytics, in contrast, is the application of business intelligence in education and emphasizes analytics at institutional, regional, and international levels.”
I like the distinction that is being made here. Learning analytics is focused on the learning process – for example, identifying learners who are struggling. Whilst academic analytics is focused on using institutional level data to understand the institution. The latter might include benchmarking an institutions academic performance against other institutions, or using attendance data to find which classes have poor attendance. In any case, academic analysis is the way I have seen business intelligence used in education so far.
George goes on to include a table which clarifies these distinctions further:
Learning Analytics and Knowledge 2012 Course
If you are interested in finding out more about learning analytics, the Society for Learning Analytics Research is offering a free open online course, Learning Analytics and Knowledge 2012.
The course is offered as a “Massive Open Online Course” (MOOC) which I think is a really cool concept. It essentially a distributed course, which links to content which can be found all over the web. It encourages collaboration through the use of social tools such as blogs, twitter and Diigo to share course links and generate your own content based on your understanding of the material. This generates a knowledge network from all the people who have taken part in the course. They’ve posted a video which explains more about what a MOOC is.
I’m really excited about the course as its an opportunity to find out about a field that is rapidly advancing and has the potential to impact education significantly over the next few years. The course has been going a few days, but you can still register. I’ll be posting links to the materials I’ve read and thoughts about learning analytics as I progress on the course.
I’ll be posting links to learning analytics resources that I find on the course and in my own research on my diigo list.