reading the discussion, I find sufficient information to know what Hunch is, and what it could do. I am not afraid to test it, but would rather invest my time in thinking about what this means for education/learning.
Hunch is a recommender system that uses your likes/dislikes to discover new relevant information objects for you. I do believe in this approach and at the same time I find this (as Stephen Dixon mentions) too simple an approach. Even though "when there is interest, learning will happen" (Arthur C Clarke), I think "stuff you like" is sometimes entirely different than "stuff you need". Edu-Hunch (or something) will keep you satisfied with recommendations about stuff you are likely to like, but will it give you an answer to a question you have? Also, "liking" itself is a very limited way of expressing your thoughts on something. You might like pizza, but no anchovis. If you dislike a Pizza Anchovis, what does the system store? On the other hand, some interesting analogies and recommendations can be done with relatively simple like/dislike statements and multiple choice answers.
If you take a Hunch-like system, but rather than expressing your interests, you are proving your expertise by answering questions, you might be able to combine interests with knowledge, a much more powerful combination in learning environments.
Some thoughts on Hunch and how something like it could become useful for education:
- Hunch should incorporate serendipity.
- As I mention above, I think that an Edu-Hunch should be combined with tools focusing on expertise/knowledge.
- We should not forget the medium and form. A very interesting topic can be delivered in a very uninteresting way, and vice versa.
I gotta go sleep now. I might add something tomorrow.
I really like your suggestion to incorporate serendipity in recommendation engines. Something to remember for the future...