The Open UniversitySkip to content
 

Big data for monitoring educational systems

Berendt, Bettina; Littlejohn, Allison; Kern, Philippe; Mitros, Piotr; Shacklock, Xanthe and Blakemore, Michael (2017). Big data for monitoring educational systems. Publications Office of the European Union, Luxembourg.

Full text available as:
[img]
Preview
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (3MB) | Preview
URL: https://publications.europa.eu/en/publication-deta...
DOI (Digital Object Identifier) Link: https://doi.org/10.2766/38557
Google Scholar: Look up in Google Scholar

Abstract

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education.

Item Type: Other
Copyright Holders: 2017 European Union
Keywords: e-learning, big data, education, learning analytics
Academic Unit/School: Learning and Teaching Innovation (LTI) > Institute of Educational Technology (IET)
Learning and Teaching Innovation (LTI)
Research Group: Health and Wellbeing PRA (Priority Research Area)
Item ID: 50930
Depositing User: Allison Littlejohn
Date Deposited: 02 Oct 2017 07:58
Last Modified: 08 Dec 2018 16:14
URI: http://oro.open.ac.uk/id/eprint/50930
Share this page:

Metrics

Altmetrics from Altmetric

Citations from Dimensions

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU