The potential benefits of learning analytics are now widely acknowledged. For example, the Higher Education Commission stated in their 2016 report that “Learning analytics has the potential to be enormously powerful for improving the student experience in university.” However, the report also recognises that “There are a number of issues and challenges facing the sector in introducing learning analytics.”
How can we move from appreciating the theoretical benefits of learning analytics to implementing these processes in practice? At a practical level how do we start to gather, collate and analyse data about student activity and transform this into an improved understanding of student learning?
This session will collaboratively explore a real-life example, examining and discussing questions asked by an academic who wants to analyse online tracking data from their module so they can understand how the students studying on the module have used the learning materials provided. The academic’s ultimate aim is to change their practice in the future, based on insights from the data. For example, should they:
* structure their teaching differently?
* provide different materials?
* change the timing or arrangement of certain aspects of the module?
* give more guidance on how to use the learning materials?
General principles of using learning analytics will be explored through this specific example, including:
* technical practicalities – what data is available? what format is it in? what tools can be used to gather, store and explore the data? how can data from different sources be combined?
* legal issues – what use can we legally make of student data? what are the GDPR requirements for gathering, processing and reporting on student data?
* ethical considerations – what use can we make of the data from an ethical standpoint? how does this differ if we wish to publish the results as a research study?
After attending this session participants should be able to discuss ethical, legal and technical issues relating to learning analytics with more confidence. They should also be aware of the key questions to consider when embarking on a learning analytics study and how to find answers within their own context, i.e. which documents or colleagues to consult for guidance.
The session will involve working in small groups of around 4-6 people to consider the questions outlined in the Session Description.
The scenario is that an academic has sent an email to their local learning technology team, requesting help with setting up a learning analytics study of the module that they have just finished teaching. The group, taking on the role of the learning technology team, will consider appropriate advice and feedback for the academic.
Summary information will be presented on each aspect based on the resources detailed above. The groups will discuss how to apply this advice to the particular situation, thus developing a deeper understanding of the concepts by applying them to a defined example. Discussion will also highlight the need to conform with local policies and practices.
Provisional outline of schedule (may be revised after local piloting)
Introduction – the questions raised by the academic – 3 minutes
Initial group discussion – 3 minutes
Considering GDPR – 5 minutes
How does GDPR impact on the current scenario? – group discussion + plenary – 10 minutes
Ethics – evaluation and research – 5 minutes
What ethical considerations need to be considered in the scenario? – group discussion + plenary – 10 minutes
Technical aspects of analytics – 5 minutes
What do we need to find out about the data? How will we process? – group discussion + plenary – 5 minutes
Summary, conclusions and Q&A – 5 minutes
BERA (2018). Ethical guidelines for educational research, fourth edition. Available at:
Educause (2016) 7 things you should know about Caliper. Available at: https://library.educause.edu/-/media/files/library/2016/3/eli7130pdf.pdf
Educause (2017) 7 things you should know about developments in learning analytics. Available at: https://library.educause.edu/-/media/files/library/2017/7/eli7146.pdf
Jisc (2015,2018). Code of practice for learning analytics. Available at: https://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics
Shacklock, X. (2016). From bricks to clicks: The potential of data and analytics in higher education. London: Higher Education Commission.
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