Learning analytics offers an alternative to these methods of gathering feedback and reports from learners. These approaches instead make use of the data left by learners and teachers as they act: their ‘trace data’. These can tell us when learners join courses, when and how they engage with online activities, view pages, borrow resources from the library, set or complete activities or assessments, and so on. Any interaction with a web-based system can be tracked, and this data could be used to better understand what learners and teachers do. The widespread use of virtual learning environments (VLEs) – also known as learning management systems (LMSs) – has meant that educational institutions now deal with increasingly large sets of data. Each day their systems gather more personal data, systems information and academic records.
Learning analytics is a field of innovative research, but it is increasingly something that many educators and institutions make use of through new tools, dashboards and reports, using online data to investigate user activity. It helps to answer questions such as:
- How many people visit the website / online learning materials?
- When do they visit / interact?
- Which links are popular?
- How many people complete the activities?
Answering the questions posed above could involve analysing large data sets from VLEs and other technologies used for learning. Learning analytics can go one step further by providing actionable insights – they take trace data from educational settings and suggest, prompt or initiate actions to improve learning and teaching. You may have heard the term ‘big data’ used in discussions of technology. It is used in a lot of different ways, but essentially means that the dataset is very large and also very complex. Because of this, it may not be possible to use a simple, traditional approach to data processing and analysis. Learning analytics of the behaviours of large numbers of students can easily fall into the category of big data. But equally, you might look at the behaviour of one class of students over a course and find that useful insights can be gained without advanced techniques and tools.
For example, in an online forum discussion associated with a particular online module or course, a VLE could capture a range of forum data, including:
- who accessed the forum
- when they did this
- how long they stayed
- what operating system they were using
- how many words they added.
Any of these data could be used to create analytics. However, only some of these analytics would be useful to teachers. It is not possible to identify which analytics will be most useful without knowing something about how the forum is being used. The presence of a learning design should identify the purpose of the forum in relation to learning outcomes. This makes it easier to decide which analytics to use.
Nkiru Banjoko