The Open UniversitySkip to content
 

Open University Learning Analytics dataset

Kuzilek, Jakub; Hlosta, Martin and Zdrahal, Zdenek (2017). Open University Learning Analytics dataset. Scientific Data, 4, article no. 170171.

Full text available as:
[img]
Preview
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (903kB) | Preview
DOI (Digital Object Identifier) Link: https://doi.org/10.1038/sdata.2017.171
Google Scholar: Look up in Google Scholar

Abstract

Learning Analytics focuses on the collection and analysis of learners’ data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students’ interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

Item Type: Journal Item
Copyright Holders: 2017 The Authors
ISSN: 2052-4463
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 53873
Depositing User: Kay Dave
Date Deposited: 19 Mar 2018 09:59
Last Modified: 08 Dec 2018 03:57
URI: http://oro.open.ac.uk/id/eprint/53873
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