My Personal Learning Network: how I learn, who I learn with, and how this may change

Creating an online version of my Personal Learning Network (PLN) has helped me realise that my learning does not happen in a straight line or within a single space. Instead, it develops through a mix of people, tools, conversations, and ideas that interact in ways I do not always plan. Mapping this network has encouraged me to think more carefully about how I learn, what I value most, and how much control I actually have over my learning.

Interaction with Others

At the centre of my PLN is interaction with others. Both online and in-person conversations with my peers play a significant role in shaping my understanding. Talking through ideas helps me understand them better and see where my understanding is unclear. Academic texts are also important, but they rarely stand alone. I tend to engage with readings alongside discussion and reflection, which helps me connect theory to real situations instead of treating it as abstract information.

A diagram showing how learning moves between individuals, digital tools, and shared conversations within a Personal Learning Network.

Digital platforms form another key part of my PLN. Online journals, discussion spaces, podcasts, and short videos allow me to engage with ideas in different ways and at different levels of depth. What I find most valuable is the flexibility to move between these sources. For example, a short video might introduce an idea, which I then explore further through reading and develop through discussion or writing. This reflects an experiential view of learning, where understanding grows through engagement and reflection (Kolb, 1984).

A visual representation of a Personal Learning Network, showing how people, digital tools, and ideas connect to support learning.

Supportive Tools

AI tools have recently become part of my learning network, but I see them mainly as supportive tools rather than sources of knowledge. They help me organise my ideas and improve clarity, but they do not replace my own judgement. In this sense, AI enhances my PLN without directing it. It supports learning by making thinking more visible, rather than by providing answers.

Overall, my PLN feels less like a clear pathway and more like a complex system. Different elements influence each other in unpredictable ways. A conversation can change how I understand a reading, while feedback can influence how I approach future learning tasks. This reflects the idea that learning develops through interaction within networks rather than through linear instruction, which is especially relevant in digital and social learning environments (Siemens, 2005).

Control & Change Within My Learning Network

Reflecting on control within my PLN has been revealing. While I choose which platforms to use and which voices to engage with, my learning is also shaped by factors such as algorithms, course structures, and assessment requirements. This means I am only partly in control of my learning. However, reflection plays an important role in maintaining agency. Choosing what to focus on or ignore is an active part of my learning.

Looking ahead 20 years, I expect my PLN to become more flexible and increasingly supported by AI. AI is likely to support my learning by connecting ideas over time, not by replacing human interaction. Even as tools change, the core of my PLN will stay the same.

Overall, mapping my PLN has helped me understand that learning is neither fully controlled nor entirely passive. It develops through interaction, reflection, and engagement with people and tools. Understanding this has helped me be more intentional about my learning and become more comfortable with uncertainty.

Reference List

Kolb, DA (1984) Experiential Learning: Experience as the Source of Learning and Development. Englewood Cliffs, NJ: Prentice Hall.

Siemens, G (2005) ‘Connectivism: A learning theory for the digital age’, International Journal of Instructional Technology and Distance Learning, 2(1), pp. 3–10.

AI Acknowledge Statement

AI tools were used to support the development of this blog in a transparent and limited way. I used prompts such as “How can a Personal Learning Network be represented as a complex system?”, “Which learning theories might help explain how someone learns within a PLN?”, and “How might AI support a learner’s PLN in the future?” to help stimulate ideas and reflection. I also used prompts to help simplify language, improve clarity, and refine the structure of the writing. All ideas were developed, selected, and shaped by me, and I made the final decisions about content, wording, and interpretation. The blog reflects my own learning, reflection, and academic judgement.