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.

Author/creator

Herodotou, Christothea

Rienties, Bart

Verdin, Barry

Boroowa, Avinash

Date

2019

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

DOI

10.18608/jla.2019.61.5

URL

Open Access Journal Webpage (Journal of Learning Analytics)

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

• Email