In my previous blog post, the architecture of learning, I outlined some of the key characteristics of learning in a digital age, and started to identify some of the main differences between Learning 1.0 (before social media) and Learning 2.0. In the summary of the article, I suggested that the distinct differences between the two types of learning are mostly based on how learners are changing the ways they interact, and their increased ability to create, share and organise their own learning. Learning 2.0 is socially much richer and more participatory, and relies more on interaction with other learners than any previous learning approach. This change has been realised through access to inexpensive internet tools that offer easy ways to connect with others of similar interest. There is a growing understanding that it's not so much what you know anymore, but who you know. No longer is the computer your only mind tool and extension of your memory - now you can also call on everyone else in the world. Social media are enabling learners everywhere to connect and work together with each other, forming convenient communities and networks of shared interest. The full power of the Learning 2.0 approach has yet to be realised, but already we are seeing radical shifts in the way learning is conducted. I also argued that if we view sequenced versions of the Web, based on the way learners use it, we will inevitably have to think of Learning 3.0, and beyond. This led me to think about what we might see in the future of learning, based on present trends, and our anticipation of what new technologies and approaches we think are on the horizon. So here we go - Learning 3.0...

Learning 3.0, if we are to believe all the hype, will be located within a semantic based architecture of webs - a 'meta-web'. I see it arising partly from what is happening on the web right now, but also as a result of new intelligent filtering tools. Increasingly, as users contribute to the content, links and pathways of the social web, it will become more 'intelligent', and will recommend to its users the best ways to find what they are looking for. It will also recommend things that users don't know they need yet, predicting their 'needs' based on their previous behaviour and choices. Learning 3.0 will see learners using sophisticated new web tools that are intricately connected to each other, are context aware, and are accessed through intuitive and natural interfaces. Here we begin to think not only of voice activated, gestural controlled interfaces, but we also need to start considering biometric recognition systems such as retinal scanning, facial recognition and even directly implanted devices that allow us to control our devices merely by thinking (see the table below). Where Learning 1.0 was organised around taxonomies and content was largely expert generated, Learning 2.0 has seen as shift toward user generated content, and the emergent property of folksonomies. We have known for some time that people learn better when they are actively engaged in making things, solving problems and engaging with others. Social media have provided the tools to achieve this on a global level.

Learning 3.0 will be user and machine generated, and will in all respects be represented in what I will call  'rhizonomies'. The rhizonomic organisation of content will emerge from chaotic, multi-dimensional and multi-nodal organisation of content, giving rise to an infinite number of possibilities and choices for learners. As learners choose their own self determined routes through the content, so context will change and new nodes and connections will be created in what will become a massive, dynamic, synthetic 'hive mind'. Here I do not refer to any strong artificial intelligence model of computation, but rather a description of the manner in which networked, intelligent systems respond to the needs of individual learners within vast, ever expanding communities of practice. Each learner will become a nexus of knowledge, and a node of content production. Extending the rhizome metaphor further, learners will act as the reproduction mechanisms that sustain the growth of the semantic web, but will also in turn be nurtured by it. Learning 3.0 will be a facet of an ongoing, limitless symbiotic relationship between human and machine.

Whatever Learning 3.0 is or will become, we can be assured it will be completely different to what has preceded it. We will witness new modes of learning, new ways of interacting and new ways of representing knowledge that will be both robust and mutable, personally contextualised, but without boundaries. I believe the future of learning is going to be very exciting indeed.

Postcript: My thinking in this blogpost is embryonic and is as ever, open to challenge. I may be hopelessly off target here, because this is uncharted territory for me. But I am taking the risk to air my views in public about this topic just to see what feedback I will receive from my professional learning network. I therefore value any dialogue (on this blog and elsewhere), corrections, advice and suggestions as I attempt to navigate my way through the thinking process about what kinds of learning we might see in the future.
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Next generation learning by Steve Wheeler is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.