A Framework for the Analysis of Personal Learning Networks

Authors

  • Nicholas S. R. Fair Knowledge Engineer, IT Innovation, University of Southampton

DOI:

https://doi.org/10.54337/nlc.v12.8640

Keywords:

Personal Learning Network, Networked learning, Analysis framework, Pedagogy, Social network analysis, Methodology

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, and information resources an individual uses for learning activities and learning goals in all learning contexts. Drawing from Education, Web Science, Digital Sociology and Network Science, a Framework was developed which conceptualises PLNs as egocentric interaction networks involving a mode, purpose and endpoint. The Framework introduces the idea of measuring the frequency of interaction along paths consisting of pre-determined, generalised nodes (and node sets). This eliminate network differences at the micro level and allows meaningful comparison and aggregation of individual PLNs into groups or whole samples.

Quantitative survey data was collected as part of a FutureLearn MOOC and in real-time converted by a bespoke mapping and visualisation tool into an online PLN map. Analysis indicates that regardless of any contextual factors, individuals interact nearly three quarters of the time via digital devices, and just a quarter of the time face-to-face or non-digitally. One third of those interactions are with smartphones, most often for the purpose of gathering information from web searches. Individuals also interact more frequently with non-humans than they do with humans. Chi-square significance testing to examine the effect of a range of external shaping factors found that the PLNs of apparently diverse groups display a considerable homogeneity. Gender, country of residence and position on the Digital Resident-Digital Visitor spectrum have no effect on the size and use of a PLN. Age and being a UK HE student have the most effect. There may also be evidence of a Network Lifecycle, with a critical period 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 PLN development in educationally and personally productive ways. If HE institutions are to respond to the networked student, living, working and learning in a network age, then no longer can the learner be considered separately from the network of people, devices, services and information resources they use for daily life. Transitioning towards a PLN-centred, networked learning HE pedagogy and learning design may arguably be the most suitable response to a study body which is increasingly and inextricably embedded in a sociotechnical reality.

Author Biography

Nicholas S. R. Fair, Knowledge Engineer, IT Innovation, University of Southampton



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Published

16-08-2024

How to Cite

Fair, N. S. R. (2024). A Framework for the Analysis of Personal Learning Networks. Proceedings of the International Conference on Networked Learning , 12, 85–95. https://doi.org/10.54337/nlc.v12.8640