Predictive Learning Analytics 'At Scale': Guidelines to Successful Implementation in Higher Education


  • Christothea Herodotou The Open University, UK
  • Bart Rienties The Open University, UK
  • Barry Verdin The Open University, UK
  • Avinash Boroowa The Open University, UK



Predictive learning analytics, higher education, distance learning, management, guidelines, adoption.


Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders (i.e., managers, teachers, students) about PLA. This paper presents an “at scale” implementation of PLA at a distance learning higher education institution and details, in particular, the perspectives of 20 educational managers involved in the implementation. It concludes with a set of recommendations about how best to adopt and apply large-scale PLA initiatives in higher education.

Author Biography

Christothea Herodotou, The Open University, UK





How to Cite

Herodotou, C., Rienties, B., Verdin, B., & Boroowa, A. (2019). Predictive Learning Analytics ’At Scale’: Guidelines to Successful Implementation in Higher Education. Journal of Learning Analytics, 6(1), 85—95.



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