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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
This paper reports on research undertaken to map and analyse Personal Learning Networks (PLNs).PLNs are the total preferred connections to the different people, technological devices, services, andinformation resources an individual uses for learning activities and learning goals in all learningcontexts. Drawing from Education, Web Science, Digital Sociology and Network Science, aFramework was developed which conceptualises PLNs as egocentric interaction networks involving amode, purpose and endpoint. The Framework introduces the idea of measuring the frequency ofinteraction along paths consisting of pre-determined, generalised nodes (and node sets). This eliminatesnetwork differences at the micro level and allows meaningful comparison and aggregation of individualPLNs into groups or whole samples.Quantitative survey data was collected as part of a FutureLearn MOOC and in real-time converted bya bespoke mapping and visualisation tool into an online PLN map. Analysis indicates that regardlessof any contextual factors, individuals interact nearly three quarters of the time via digital devices, andjust a quarter of the time face-to-face or non-digitally. One third of those interactions are withsmartphones, most often for the purpose of gathering information from web searches. Individuals alsointeract more frequently with non-humans than they do with humans. Chi-square significance testingto examine the effect of a range of external shaping factors found that the PLNs of apparently diversegroups display a considerable homogeneity. Gender, country of residence and position on the DigitalResident-Digital Visitor spectrum have no effect on the size and use of a PLN. Age and being a UKHE student have the most effect. There may also be evidence of a Network Lifecycle, with a criticalperiod of PLN growth occurring during the age of 18-25.This means that universities are ideally placed, indeed may even have a duty of care, to foster PLNdevelopment in educationally and personally productive ways. If HE institutions are to respond to thenetworked student, living, working and learning in a network age, then no longer can the learner beconsidered separately from the network of people, devices, services and information resources they usefor daily life. Transitioning towards a PLN-centred, networked learning HE pedagogy and learningdesign may arguably be the most suitable response to a study body which is increasingly andinextricably embedded in a sociotechnical reality
Personal Learning Networks
Fair, Nic
743fd34e-7e2b-42d0-818e-1db641e789be
Fair, Nic
743fd34e-7e2b-42d0-818e-1db641e789be

Fair, Nic (2020) A framework for the analysis of personal learning networks. 12th International Conference on Networked Learning, virtual. 18 - 20 May 2020.

Record type: Conference or Workshop Item (Other)

Abstract

This paper reports on research undertaken to map and analyse Personal Learning Networks (PLNs).PLNs are the total preferred connections to the different people, technological devices, services, andinformation resources an individual uses for learning activities and learning goals in all learningcontexts. Drawing from Education, Web Science, Digital Sociology and Network Science, aFramework was developed which conceptualises PLNs as egocentric interaction networks involving amode, purpose and endpoint. The Framework introduces the idea of measuring the frequency ofinteraction along paths consisting of pre-determined, generalised nodes (and node sets). This eliminatesnetwork differences at the micro level and allows meaningful comparison and aggregation of individualPLNs into groups or whole samples.Quantitative survey data was collected as part of a FutureLearn MOOC and in real-time converted bya bespoke mapping and visualisation tool into an online PLN map. Analysis indicates that regardlessof any contextual factors, individuals interact nearly three quarters of the time via digital devices, andjust a quarter of the time face-to-face or non-digitally. One third of those interactions are withsmartphones, most often for the purpose of gathering information from web searches. Individuals alsointeract more frequently with non-humans than they do with humans. Chi-square significance testingto examine the effect of a range of external shaping factors found that the PLNs of apparently diversegroups display a considerable homogeneity. Gender, country of residence and position on the DigitalResident-Digital Visitor spectrum have no effect on the size and use of a PLN. Age and being a UKHE student have the most effect. There may also be evidence of a Network Lifecycle, with a criticalperiod of PLN growth occurring during the age of 18-25.This means that universities are ideally placed, indeed may even have a duty of care, to foster PLNdevelopment in educationally and personally productive ways. If HE institutions are to respond to thenetworked student, living, working and learning in a network age, then no longer can the learner beconsidered separately from the network of people, devices, services and information resources they usefor daily life. Transitioning towards a PLN-centred, networked learning HE pedagogy and learningdesign may arguably be the most suitable response to a study body which is increasingly andinextricably embedded in a sociotechnical reality

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More information

Published date: 20 May 2020
Venue - Dates: 12th International Conference on Networked Learning, virtual, 2020-05-18 - 2020-05-20
Keywords: Personal Learning Networks

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Local EPrints ID: 472906
URI: http://eprints.soton.ac.uk/id/eprint/472906
PURE UUID: 85a96d2d-bef1-4344-b03c-e64cdde0b232
ORCID for Nic Fair: ORCID iD orcid.org/0000-0003-1566-4689

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Date deposited: 05 Jan 2023 18:09
Last modified: 17 Mar 2024 03:26

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Author: Nic Fair ORCID iD

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