The University of Southampton
University of Southampton Institutional Repository

How should we measure online learning activity?

How should we measure online learning activity?
How should we measure online learning activity?
The proliferation of Web-based learning objects makes finding and evaluating resources a considerable hurdle for learners to overcome. While established Learning Analytics methods provide feedback that can aid learner evaluation of learning resources, the adequacy and reliability of these methods is questioned. Because engagement with online learning is different from other Web activity, it is important to establish pedagogically relevant measures that can aid the development of distinct, automated analysis and visualization systems. Content analysis is often used to examine online discussion in educational settings, but these instruments are rarely compared with each other which leads to uncertainty regarding their validity and reliability. In this study, participation in MOOC comment forums was evaluated using four different analytical approaches: the DiAL-e framework, Bloom’s Taxonomy, Structure of Observed Learning Outcomes (SOLO) and Community of Inquiry (CoI). Results from this study indicate that different approaches to measuring cognitive activity are closely correlated and are distinct from typical interaction measures. This suggests that computational approaches to pedagogical analysis may provide useful insights into learning processes.
2156-7069
1-28
O'Riordan, Tim
d6ba191a-e432-41f8-b3da-176d28355579
Millard, David E.
4f19bca5-80dc-4533-a101-89a5a0e3b372
Schulz, John B.
a587472f-dde4-42fb-bc32-08d208d7fdf7
O'Riordan, Tim
d6ba191a-e432-41f8-b3da-176d28355579
Millard, David E.
4f19bca5-80dc-4533-a101-89a5a0e3b372
Schulz, John B.
a587472f-dde4-42fb-bc32-08d208d7fdf7

O'Riordan, Tim, Millard, David E. and Schulz, John B. (2016) How should we measure online learning activity? Research in Learning Technology, 24, 1-28, [30088]. (doi:10.3402/rlt.v24.30088).

Record type: Article

Abstract

The proliferation of Web-based learning objects makes finding and evaluating resources a considerable hurdle for learners to overcome. While established Learning Analytics methods provide feedback that can aid learner evaluation of learning resources, the adequacy and reliability of these methods is questioned. Because engagement with online learning is different from other Web activity, it is important to establish pedagogically relevant measures that can aid the development of distinct, automated analysis and visualization systems. Content analysis is often used to examine online discussion in educational settings, but these instruments are rarely compared with each other which leads to uncertainty regarding their validity and reliability. In this study, participation in MOOC comment forums was evaluated using four different analytical approaches: the DiAL-e framework, Bloom’s Taxonomy, Structure of Observed Learning Outcomes (SOLO) and Community of Inquiry (CoI). Results from this study indicate that different approaches to measuring cognitive activity are closely correlated and are distinct from typical interaction measures. This suggests that computational approaches to pedagogical analysis may provide useful insights into learning processes.

Text
1761-Article Text-8498-1-10-20160728 - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)
Text
RLT_180216.pdf - Other
Available under License Other.
Download (422kB)
Text
Final_RLT_230516_eprints.pdf - Other
Download (420kB)

More information

Submitted date: 18 February 2016
e-pub ahead of print date: 29 July 2016
Published date: 2016
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 390338
URI: http://eprints.soton.ac.uk/id/eprint/390338
ISSN: 2156-7069
PURE UUID: daa2e480-c2d8-4ded-b67c-0085eff60cb0
ORCID for Tim O'Riordan: ORCID iD orcid.org/0000-0003-4905-7430
ORCID for David E. Millard: ORCID iD orcid.org/0000-0002-7512-2710

Catalogue record

Date deposited: 24 Mar 2016 11:42
Last modified: 15 Mar 2024 02:59

Export record

Altmetrics

Contributors

Author: Tim O'Riordan ORCID iD
Author: David E. Millard ORCID iD
Author: John B. Schulz

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×