Predictive Learning Analytics 'At Scale': Guidelines to Successful Implementation in Higher Education
Item
- Title
- Predictive Learning Analytics 'At Scale': Guidelines to Successful Implementation in Higher Education
- Abstract/Description
- 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.
- Date
- In publication
- Journal of Learning Analytics
- Volume
- 6
- Issue
- 1
- Pages
- 85-95
- Resource type
- en Research/Scholarly Media
- Resource status/form
- en Published Text
- Scholarship genre
- en Empirical
- Keywords
- adoption.
- Language
- en
- Open access/full-text available
- en Yes
- Peer reviewed
- en Yes
- ISSN
- 1929-7750
- Citation
- 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), Article 1. https://doi.org/10.18608/jla.2019.61.5
- Rights
- Copyright (c) 2019 Journal of Learning Analytics
- Item sets
- Handbook Chapter 20 Citations
Annotations
There are no annotations for this resource.