Learning networks are about social search

Damon Horowitz and Sepandar Kamvar recently published a paper – referentially entitled “The Anatomy of a Large-Scale Social Search Engine” (PDF) – in which they nicely lay out the social search problem and the Aardvark solution. As I was reading this paper, one thought kept surfacing: Learning networks are about social search.

It seems reasonable to claim that since Q&A is about learning, Aardvark’s network-based Q&A site can be described as a type of learning network. The less obvious but, in my opinion, more interesting claim is that the design of learning networks can (and should!) be viewed as a social search problem. Illich argued this, Meetup demonstrates it quite nicely, and Grockit is moving in that direction, too. In an email exchange published last year, I suggested that the future of AI in Education will have a lot to do with social search:

I think the AIED systems of the future will be less about teaching directly, and more about providing guidance: when and how a student would benefit from working with someone else (perhaps a teacher, tutor, or peer.) When I get stuck solving a particular type of problem, who (that’s online and available) can best help me understand it? A good system will have predicted the frustrating challenge, and will have already lined up the person best-suited to explaining it to me in a way that I will understand. After I’ve demonstrated that I mastered the necessary skills, who can I then explain it to, both to help them and to clarify it for myself? A good system will be able to seamlessly coordinate this process. Through these interactions, the system will unobtrusively be learning more about me – both as a learner and as a peer-tutor – in order to improve with time.

Downright Aardvarkian.