Framing a learning network as relational (drawing on Bruno Latour) can radically open learning to the complex web of interdependencies that exist across teachers, students, institutions, ecosystems, cultures, experiences, and indeed all parts of a learning network. In the context of practice-led learning, such networks underscore that learning is a shared endeavour grounded in authentic relationship – often through community practice, service, or shared activity inclusive of a full diversity of stakeholders allowing learning to be a cooperative evolving process influenced by multiple actors. 

Receptive network ontologies further acknowledge the importance of openness to new ideas and different viewpoints in learning. The synergy between relational and receptive networks empowers learners to actively engage with a range of information sources and build their unique understanding. This shifts learners from passive recipients to active contributors and empowering them to explore, share, interrogate, and critically scrutinise information, practice, and experiences.

The combination of relational and receptive network ontologies offers a potent theoretical structure for understanding and promoting a reimagined learning paradigm that foregrounds relationship, receptivity co-creation and collaboration in an authentically distributed framework. Acknowledging learners’ interconnectedness and their openness to a diversity of knowledge and experience allows the co-creation of inclusive and participatory educational spaces.

Interweaving relational and receptive network ontologies emphasises learners, their agency, interconnectedness, and openness to diverse perspectives. By adopting this perspective, a de-institutionalised learning paradigm – such as a distributed network – can foster an environment that promotes active learning, collaboration, and critical engagement. Specifically, it can empower exploration in the following areas:

• Distributed Agency: Agency would be distributed among all nodes – student, teacher,  human and more-than-human, treating each as a valid and capable participant. This could translate into a network where participants are not just passive receivers and providers of information, but active participants that engage and shape the network in unique ways. Beyond an emphasis on nodes, the receptivity of such a network would give equal agency to connections and relationships as to objects in relation. 
• Collaborative Learning: A relational and distributed learning network would emphasize collaborative, experiential, and embodied learning. The network could facilitate interactive experiences, encourage peer-to-peer learning, and even integrate with physical or augmented reality environments to support embodied learning experiences.
• Fluid and Dynamic Structures: Such a network would also have a fluid and dynamic structure, reflecting the constant flux and change of ecological complexity. Rather than being fixed and static, the network would continually adapt and evolve in response to the actions and interactions of its participants – human and more-than-human (from Aardvark to Albedo to AI)
• Ethical and Inclusive Design: A key element braided together within an authentically de-institutionalised distributed network model is a foundation of ethical, inclusive, accessible and equitable design principles. The network would be designed to inclusively evolve, giving all nodes a voice in shaping network changes, and ensuring that adaptations don’t disadvantage certain groups. New identities that blend definitions of learner, teacher, and co-creator roles would be valued within the network and contribute to a diverse, vibrant learning ecosystem. Any accessible network would also engage in what EF Schumacher described as ‘appropriate technologies’, here in the context of minimal computing to empower ‘students to be their own arbiters of engagement’ (​​Lee Skallerup Bessette).
• Development of new network identities: Finally, such a network (inspired as it is by the work of Karen Barad, Felix Guattari, Bruno Latour, Thomas Nail, Rosi Braidotti, Jussi Parikka and others) would necessarily break down barriers between node and relationship; between human and more-than-human; between learning and experience. A receptive relational network could yield an evolution in network identities, an ‘ecology of practices’ that  ‘opens up a world: a world of relations, abstractions, spaces that turn into movements … and it becomes an onto-epistemological framework’ (Parikka).

Inroads into the development of distributed and relational learning are not entirely uncommon; however, engaging with dynamic learning networks in the context of institutional frameworks can prove challenging. Nonetheless, there are huge opportunities for learning in innovative network ecologies if learning is to continue to develop as a meaningful way to engage in the global ecological and social challenges that increasingly come to define this century.