With the ascension of adaptive learning in combination with increasingly digital learning environments, we would view the ‘rehumanization’ of the learning space as a compelling option for addressing the attendant challenges. This would entail the promotion of productive crowdsourcing learning networks whereby individuals are able to elicit answers or input from a globally dispersed community of learner-users. These communities would be self-organising and self-regulating and capable of providing quick and reliable feedback to an individual learner’s needs. This ecosystem of P2P connections would act as an organic filter for the learner, collaboratively curating the vast amount of information available and providing responses and recommendations based on collective experience.
An adaptive learning layer may be added to this model that would then make recommendations or suggestions based on the learner’s online history or search behaviour. Rather than making suggestions in the form of content chunks to cover, however, the adaptive learning layer could suggest topics, themes or areas of study that are relevant or related to the material the learner is choosing to interact with. In a sense the adaptive learning element would become a virtual curriculum developer that responded to the preferences of the individual learner.
In addition, the evolution of the Semantic Web by the World Wide Web Consortium (3WC) will potentially provide an in-built solution to navigating the vast amount of data when looking for applicable learning material. The Semantic Web will present online data in terms of relationships and relevance rather than as straightforward text-based search criteria. A learner will be able to engage with online content that understands what they are looking for and how it relates to and impacts other topics.