Extended cognition is now a reality with rise of social web. Smart devices and emerging collective intelligence is aiding us to take part in tasks much bigger than we can naturally handle. In the age of digital natives, learning is the most affected process by this phenomenon, and has created a void in this space to rethink the model to suit the generation of web. Current educational model is not future proof as its creating more autonomous problem solvers, while future demands high caliber people to collaborate on interdisciplinary problems with potential global impact. Primary motto of this learning model is to develop critical thinking and continuous learning among individuals. Can such process be engineered in the first place? If ones goal is to attain the formal derivatives, what are the possible ways to realize it? Current paper discusses along with the generic web learning trends, a model based on Rhizomatic learning and contextual relations generated from similarity sets of social networks. This unique approach emphasizes more on distance among the similar sets to promote maximum diversity in the learning flows. Also leverages our earlier work, a feedback framework designed to judge diverse facets of a personality from interactions on the web
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