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A framework for the analysis of personal learning networks

A framework for the analysis of personal learning networks
A framework for the analysis of personal learning networks
In these critical Covid-19 times, HE institutions need to respond to the transition to online and blended learning and the networked student. This chapter presents an analysis of the size, use and preferences of Personal Learning Networks (PLNs). Using a novel Framework which conceptualises PLNs as egocentric interaction networks consisting of an Interaction Mode, an Interaction Purpose and an Interaction Endpoint and indicating Network Size (number of nodes), Network Use (interaction frequency) and Network Preferences.

Quantitative survey data was collected through the ‘Learning in the Network Age’ FutureLearn MOOC from 842 individuals in 92 different countries, with responses visualised in real-time as online network maps. Statistical analysis indicated that where we live, our attitude to technology, and whether we are at work or leisure significantly affects the size of our PLN. How we use our PLN is significantly impacted by our gender, life stage, main activity and attitude to technology. This causes differences in the size and use of a PLN. In contrast, our interaction preferences are barely impacted by any of these factors and shows considerable homogeneity between diverse people.

The data also indicated that HE student’s networks undergo growth and important changes to use and interaction preference on entering University.
211-236
Springer
Fair, Nicholas
743fd34e-7e2b-42d0-818e-1db641e789be
Bonderup, Nina
Hansen, Jens Jorgen
Hansen, Stig Borsen
Ryberg, Thomas
de Laat, Martin
Fair, Nicholas
743fd34e-7e2b-42d0-818e-1db641e789be
Bonderup, Nina
Hansen, Jens Jorgen
Hansen, Stig Borsen
Ryberg, Thomas
de Laat, Martin

Fair, Nicholas (2021) A framework for the analysis of personal learning networks. Bonderup, Nina, Hansen, Jens Jorgen, Hansen, Stig Borsen, Ryberg, Thomas and de Laat, Martin (eds.) In Conceptualising and Innovating Education and Work with Networked Learning. Springer. pp. 211-236 . (doi:10.1007/978-3-030-85241-2_12).

Record type: Conference or Workshop Item (Paper)

Abstract

In these critical Covid-19 times, HE institutions need to respond to the transition to online and blended learning and the networked student. This chapter presents an analysis of the size, use and preferences of Personal Learning Networks (PLNs). Using a novel Framework which conceptualises PLNs as egocentric interaction networks consisting of an Interaction Mode, an Interaction Purpose and an Interaction Endpoint and indicating Network Size (number of nodes), Network Use (interaction frequency) and Network Preferences.

Quantitative survey data was collected through the ‘Learning in the Network Age’ FutureLearn MOOC from 842 individuals in 92 different countries, with responses visualised in real-time as online network maps. Statistical analysis indicated that where we live, our attitude to technology, and whether we are at work or leisure significantly affects the size of our PLN. How we use our PLN is significantly impacted by our gender, life stage, main activity and attitude to technology. This causes differences in the size and use of a PLN. In contrast, our interaction preferences are barely impacted by any of these factors and shows considerable homogeneity between diverse people.

The data also indicated that HE student’s networks undergo growth and important changes to use and interaction preference on entering University.

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More information

Published date: 15 December 2021

Identifiers

Local EPrints ID: 456280
URI: http://eprints.soton.ac.uk/id/eprint/456280
PURE UUID: ce9cd1c5-209f-49f1-ad8f-39ca941fde74
ORCID for Nicholas Fair: ORCID iD orcid.org/0000-0003-1566-4689

Catalogue record

Date deposited: 27 Apr 2022 01:00
Last modified: 27 Apr 2022 01:55

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Contributors

Author: Nicholas Fair ORCID iD
Editor: Nina Bonderup
Editor: Jens Jorgen Hansen
Editor: Stig Borsen Hansen
Editor: Thomas Ryberg
Editor: Martin de Laat

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