“What have we learned from 6 years of implementing learning analytics amongst 100.000+ students?”By Professor Bart Rienties, Head of Academic Professional Development, Institute of Educational Technology, The Open University, UK |
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Abstract
The Open University UK (OU) has been implementing learning analytics since 2014, starting with one or two modules to its current practice of large-scale implementation across all its 400+ modules and 170.000+ students and 4000+ teaching staff. While a range of reviews (e.g., Adenij, 2019) and scholarly repositories (e.g., Web of Science) indicate that the OU is the largest contributor to academic output in learning analytics in the world, behind the flashy publications and practitioner outputs there are a range of complex issues in terms of ethics and privacy, data infrastructures, buy-in from staff, student engagement, and how to make sense of big data in a complex organisation like the OU.
Based upon large-scale big data research we found some interesting tensions in both design and educational theory, such as:
– 69% of engagement by students on a week by week basis is determined by how teachers are designing courses (i.e., learning design and instructional design indeed directly influence behaviour and cognition), but many teachers seem reluctant to change their learning design based upon data of what works and what does not work (e.g., making sense of data, agency);
– How teachers engage with predictive learning analytics (PLA) significantly improves student outcomes, but only a minority of teachers actually use PLA;
– Some disadvantaged groups engage more actively in OU courses, but nonetheless perform lower than non-disadvantaged students.
During this CELDA keynote I would like to share some of my own reflections of how the OU has implemented learning analytics, and how these insights are helping towards a stronger evidence-base for data-informed change. Furthermore, by sharing some of the lessons learned from implementing learning analytics on a large scale I hope to provide some dos and don’ts in terms of how you might consider to use data in your own practice and context.
Bio
Dr. Bart Rienties is Professor of Learning Analytics and head of Academic Professional Development at the Institute of Educational Technology at the Open University UK. As Associate Director he leads a group of academics who provide university-wide academic professional development and innovation courses and conduct evidence-based research of how professionals learn. As educational psychologist, he conducts multi-disciplinary research on work-based and collaborative learning environments and focuses on the role of social interaction in learning, which is published in leading academic journals and books. His primary research interests are focussed on Learning Analytics, Professional Development, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He has successfully led a range of institutional/national/European projects, and has received a range of awards for his educational innovation projects. He has published over 200 academic outputs, and is the 4th most cited author and contributor in Learning Analytics in the period 2011-2018 (Adeniji, 2019), the 5th most published author on internationalisation in the period 1900-2018 (Jing et al. 2020), the 7th most published author on social network analysis in social sciences in the period 1999-2018 (Su et al. 2020), and the 14th most published author on educational technology in the period 2015-2018 (West & Bodily, 2020).
For more information check his website at https://iet.open.ac.uk/