With regulatory changes in the world of Legal Education, BPP University Law School is currently redesigning all its programmes. These new programmes take a blended approach to learning, with Learning Technologies playing an increasingly important role. This ambitious project and its use of Learning Technologies to facilitate learning activities will generate huge amounts of data. A supporting project at BPP is commoditising this data generation developing Learning Analytics. The Law School is using these Learning Analytics to create an Intervention Toolkit that supports the academic success and wellbeing of our Learners.
In broad terms, 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’ (Siemens & Gasevic, 2012). With some analytics-based interventions reportedly unsuccessful (Sønderlund, Hughes & Smith, 2019), and with this wealth of data at our disposal, what actions should we take to ensure effective support our Learners? For example, when and how should we intervene? Effective interventions are a priority, but to develop these we need to explore what data to collect, how it should be analysed and by whom should it be reported?
The Higher Education Commission (2016) reported on the benefits of Learning Analytics to improve Student Experience but recognised there are still ‘a number of issues and challenges facing the sector’. BPP University occupies a unique position among Higher Education Institutions. The focus on professional education means that a significant proportion of our Learners are sponsored by their Employers, our Clients. The commercial relationship with our Clients raises additional considerations around reporting and the extent of disclosure. These Learner concerns impact on the role of the Personal Tutor to the detriment of student wellbeing. Ahern (2018) recognises the key role of the Personal Tutor in the student experience. How will the Personal Tutor role develop with the introduction of Learning Analytics with approaches that are both effective and ethical?
This reflective session will explore the ethical and safety considerations around Learner data capture and Learner interventions. We’ll share the results of our Project Pilot and ask participants to contribute their perspectives on data driven learner interventions in Higher Education. Through open discussion, polls and opportunity for anonymous comment we’ll get a snapshot of participant views on the following questions:
- Data Security – who should have access, why, when and how?
- What ethical implications should we consider in the collection of learner data and sharing with sponsors, employers and others?
- There are hidden dangers when coupling Learner interventions and data, but what unintended consequences should we consider?
- What is the impact of Learning Analytics on the role of the Personal Tutor? What additional support will Personal Tutors need?
- How, with ever increasing pressure on time and resources, we can avoid ‘intervening by numbers’ and promote effective, ethical Learner Interventions?
Participants will reflect on their own views on Learning Analytics and Learner Interventions and debate those views with colleagues with consideration for the impact on their own practice.
The session will open with a brief description of the BPP University Law School redesign project, the approaches and technologies involved and an overview of the approach to Learning Analytics at BPP to introduce the results of the Project Pilot from May 2020.
Participants will be surveyed through their own devices, enabling them to share their headline views on Learning Analytics and Learner Interventions. This serves the purpose of providing a platform to explore the collective views on ethical and safety considerations in the use of Learning Analytics, Learner Interventions and the impact of data. The survey will seek to provide a general quantitative perspective on the views of the use of data in supporting and/or driving interventions.
The results of this live survey will be openly broadcast and available for all participants, enabling individuals and groups to identify areas of agreement and disagreement. These areas will be opened for further participant debate. The areas chosen will be on the themes of learning, wellbeing and ethics. To promote debate, areas will be chosen where there is a broader range in perspectives across the group. The debate will ask individuals to promote their personal views, the findings of their own informal and formal research as well as the output of projects they have worked on individually or as part of their involvement in initiatives at their own institutions.
This live session will look to culminate in key statements that focus on the aforementioned themes, highlighting key areas of broad agreement as well as stressing the importance of transparency in disagreement to explore opposing views in more detail. These key outputs will move beyond the live session, written up into an open blog where we will invite participants of the session, and the wider community, to contribute further views and wider reading. This post will again focus on the key themes identified and look to promote a further session in the ALT Winter Conference in the form of a Tweet Chat, or similar, to follow up on the lessons learnt from the initial rollout of the new BPP Law School programmes and Intervention Toolkit, and to reflect on our earlier views on Learner Interventions and data.
Sønderlund, A., Hughes, E. & Smith, J., 2018. The efficacy of learning analytics interventions in higher education: A systematic review. British Journal of Educational Technology, 50(5), pp. 2594-2618.
Ahern, S., 2018. The potential and pitfalls of learning analytics as a tool for supporting student wellbeing. The Journal of Learning and Teaching in Higher Education, 1(2), pp. 165-172.
Siemens, G. & Gasevic, D., 2012. Guest editorial-Learning and knowledge analytics. Educational Technology & Society, 15(3), pp. 1-2.