In the July 2021 edition of Edubytes, we explore learning analytics — a topic that has seen a leap in interest following the shift to online teaching and learning — and new challenges it must face to continue to meaningfully support teaching, learning and learning design.
Our guest editors are Dr. Halimat Alabi and Dr. Leah Macfadyen of the Master of Educational Technology program in the UBC Faculty of Education, and Craig Thompson, from UBC’s learning analytics team. All three have contributed to learning analytics (LA) research and practice, and the work of the Society for Learning Analytics Research (SoLAR).
What is learning analytics?
2020 was a landmark year in education; the ramifications of international world-wide emergency remote teaching will likely be felt for years to come. Educators urgently sought out tools and techniques to support teaching, learning, and learning design in both familiar and radically new (to them) contexts. And in this rapidly evolving digital landscape of education, many were drawn to learning analytics (LA) — an already diverse field of research and practice that the Society for Learning Analytics Research (SoLAR) defines as:
“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.”
LA is focussed on the learner and on learning environments. Its many approaches make use of data from learning management and student information systems, as well as a wide range of additional tools and technologies that may be employed in teaching and learning.
Image credit: Stian Håklev (@houshuang) and Giulia Forsythe (@giuliaforsythe)
It explores learner choices and behaviours in a variety of learning contexts, and a decade of research has offered tantalizing glimpses into the potential affordances of LA: increased formative feedback to instructors, faster identification of learners in need of additional support, empowerment of learners to manage their own learning, illumination of curriculum connectivity and alignment, improved assessment of learning, and evidence to support academic planning.
- New to LA? Dive into introductory material and examples in the new and accessible Learning Analytics 101 resource from NYU.
At the same time, in a year filled with so much uncertainty and socio-political turmoil, attitudes towards and relationships to data and analytics have been significantly altered. Three critical challenges that impact our efforts to make best use of learning data to support teaching and learning include:
- the reality that learning environments and learning technology ecosystems are rapidly evolving;
- continuing evidence that accurate predictions are difficult;
- and the cold hard truth that data is not neutral.
The Society for Learning Analytics Research (SoLAR)
Internationally, much of the research, thinking and scholarship in the field of LA is supported by SoLAR, an international, inter-disciplinary network of researchers, educators, and educational stakeholders invested in the application of learning analytics to improve teaching and learning.
Since 2011, SoLAR has organized the annual International Conference on Learning Analytics & Knowledge (LAK) and the Learning Analytics Summer Institute (LASI), launching multiple initiatives to support collaborative and open LA research, promoting the publication and dissemination of learning analytics research, and advising and consulting with governments.
- For bite-sized introductions to current issues in LA, check out the SoLAR podcast and SoLAR webinar series.
UBC was a founding member of SoLAR, and our continuing Institutional Membership allows all current UBC students, instructors, and staff eligibility for free SoLAR membership.
UBC hosts the international 2021 Learning Analytics Summer Institute
From June 21–25, UBC and SoLAR co-hosted the 2021 Learning Analytics Summer Institute (LASI) as a week-long, fully virtual event. This year’s LASI was the largest and most geographically diverse ever, owing to its fully-online format. 226 attendees from 27 countries took part, and 79% of the participants were first-time LASI attendees.
- Watch the keynote presentation, How can teachers monitor and support students from a distance?, given by Dr. Christothea Herodotou of the UK Open University.
Learning analytics practitioners and practice
Who is ‘doing’ LA in our universities, and what are they doing with it?
- Listen to “Learning Analytics Practitioners and Practice”, the latest episode (#12) of SoLAR’s Spotlight podcast series. It features this article’s guest co-editor Leah Macfadyen, and Danny Liu from the University of Sydney, Australia, chatting about who LA practitioners are and the pragmatics of translating LA research into real classroom practice.
How has COVID disrupted analytics?
What have we learned in this COVID year about effective analytics strategies? Meaningful accurate prediction of learner success was already challenging, even when multiple years of ‘normal’ data were available. But in the educational chaos catalyzed by the COVID pandemic, historic data has often been unhelpful.
- Read how the COVID pandemic has changed analytics practices in the business world in MIT’s Sloan School of Management interview with business professors Dr. Thomas Davenport and Dr. Jeffery Camm. They describe the ways that organizations are currently using data (more descriptive and less predictive analytics) in turbulent conditions. Can we expect a similar shift in education? How can we analyze and visualize learner success in an uncertain future?
No such thing as neutral data
How do we use predictive analytics to support historically under-served learners? Can we trust learning data and analytic algorithms to generate meaningful predictions that don’t simply replicate existing inequalities and reinforce beliefs about ‘kinds of learners’?
- Watch Shalini Kantayya’s new documentary film Coded Bias. The film follows MIT Media Lab computer scientist Dr. Joy Buolamwini, along with data scientists, mathematicians, and watchdog groups from all over the world, as they fight to expose the discrimination within algorithms which they argue are now prevalent across all spheres of daily life.
- Dr. Buolamwini presents more of her work in her TED Talk How I’m fighting bias in algorithms.
- Should predictive models of student outcomes be ‘colour-blind’? Taking up the theme for the world of education, LA researcher Dr. Simon Buckingham Shum (University of Technology Sydney, Australia) questions the current design of predictive models and asks: do models that do not include demographic data actually help students from marginalized groups more than models that do?
Enjoyed reading about learning analytics in the COVID era? Learn about other topics we covered in the July 2021 edition by reading the complete Edubytes newsletter. To view past issues, visit the Edubytes archive.
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