Group Admins
Description
Session Description
In this workshop the presenters will take participants through a hands-on experience of using learning analytics to inform a real-time intervention on a large-scale distance-learning course. The Learning Design Team at a Distance Learning Institution in the UK uses the Analytics for Action (A4A) process, based on published research (Rienties et al., 2015), to assist module teams in understanding how students are progressing on their course, and to support them in making interventions to improve student retention, satisfaction, and success, based on the data.
In the workshop, delegates will be guided through the A4A process and will use it to recommend actions or further investigations in response to any issues they identify.
Objectives of the workshop
• To understand how learning analytics can be used to provide a picture of student engagement on a distance-learning course
• To understand how to use learning analytics to inform changes to a live course
• To gain hands-on practice of using learning analytics
• To understand more about the practical and ethical considerations about making changes mid-course
Please note, this session will focus on the learning and teaching perspective on analytics – evaluating and choosing suitable analytics software for your institution, for example, will not be covered (like many large educational institutions, The Open University has dedicated teams looking after this side of the business). Whilst the Open University has teams accountable for the stewardship and protection of data, we will touch on these points during the presentation with reference to the following resources and policy documents:
• https://help.open.ac.uk/how-the-ou-uses-student-data
• https://help.open.ac.uk/learning-analytics-and-you
• http://www.open.ac.uk/students/charter/sites/www.open.ac.uk.students.charter/files/files/using-information-to-support-student-learning.pdf (printed copies of this leaflet will be available to participants)
• http://www.open.ac.uk/students/charter/sites/www.open.ac.uk.students.charter/files/files/ethical-use-of-student-data-policy.pdf
• http://www.open.ac.uk/students/charter/sites/www.open.ac.uk.students.charter/files/files/ethical-student-data-faq.pdf
It is also important to note all members of staff using Open University Analytics data must have successfully completed GDPR training.
Session content: evaluation and reflection
Learning analytics is a widely published topic in higher education research , and much has been written about its potential uses and benefits, as well as the challenges of analytics (Ferguson, 2012). Developing a framework that considers different dimensions, including a holistic view of the data, the users and the process have also been considered (Greller and Drachsler, 2012).
Recent Open University research has focused on how the benefits of learning analytics can be successfully applied in practice combining each of these dimensions (Rienties et al., 2015), and as a result we have now embedded the Analytics for Action (A4A) approach in the module review process. This approach has learning analytics at its heart, but it also engages with staff in such a way as to support them in their use of data and to provide them with a clear process and practical recommendations for enhancing their distance-learning course to improve student retention, satisfaction, and success.
This engagement with staff comes from a twofold approach to support. First, face-to-face, hands-on training, where staff are supported in taking their first steps in exploring learning analytics data to understand how their module is performing and how students are engaging with it. Secondly, via a series of data support meetings held during the presentation of a module where the module team are assisted in developing insight into their module and in identifying the actions that may help to improve the module’s performance.
By providing delegates with a hands-on experience of the training and the process that we run for internal staff, we aim to help them understand how they could take forward use of learning analytics in their own institution, particularly in relation to supporting in-presentation change. Following on from the hands-on activities, delegates will discuss how they might adapt the approach to their own institution and consider some of the challenges they may need to overcome to achieve this – including ethical issues and the impact of GDPR. Including this as part of the workshop will not only give them access to the workshop facilitators’ expertise and advice, but also facilitate peer-to-peer knowledge sharing among participants, who will have varying levels of experience of working with learning analytics.
Finally, this workshop will help delegates to implement their own solutions, to recognise the importance of the human dimensions to this area of work, and to recognise that it’s not simply about providing tools and a process.
• Introduction and background to A4A (10 minutes)
• Hands-on activity 1 (15 minutes)
• Activity introduction
• Delegates will be provided with analytics dashboard data relating to a distance- learning course and asked to undertake Phase 1 of our Analytics for Action process – reviewing data
• Wrap-up discussion around this phase of the process
• Hands-on activity 2 (15 minutes)
• Delegates will be provided with analytics dashboard data relating to the same course and asked to undertake Phase 2 of our A4A process – investigating issues
• Discussion on the approach and fit with own institutional context (in groups) (10 minutes)
• Conclusion (10 minutes)
References
• Ferguson, R. (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5), 304-317. doi: 10.1504/ijtel.2012.051816
• Greller, W. and Drachsler, H. (2012) Translating Learning into Numbers: A Generic Framework for Learning Analytics, Educational Technology & Society, Vol. 15(3), p.42-57.
• Lockyer, L., Heathcote, E. & Dawson, S. (2013) Informing pedagogical action: aligning learning analytics with learning design. American Behavioral Scientist, Vol. 57(10), 1439-59.
• Rienties, B., Boroowa, A., Cross, S., Kubiak, C., Mayles, K., & Murphy, S. (2015). Analytics4Action Evaluation Framework: a review of evidence based learning analytics interventions at Open University UK. Journal of Interactive Media in Education.
