You’re probably aware of the TED talks – short talks by interesting people that then get posted to the web. I came across one recently by Sugata Mitra, an Indian professor / educator who did an experiment where he put computers into Indian slums and walked away, with a video camera recording what happened afterwards. The results are summarized in the CNN article here, and the talk is fun and worth watching.
While the grander conclusions are a bit exaggerated in the talk, it does make a powerful argument for constructivist learning – giving kids tools and letting them figure things out for themselves. It’s pretty impressive what the kids he watches can learn on their own, with almost no guidance, on out-of-the-box computers, sometimes loaded with tutorials, and sometimes with minimal help from a “granny cloud”.
I suspect that if you probed, these kids would have large gaps in their understanding compared to kids with a good teacher around, but apparently they don’t have more gaps than kids with a not-so-good teacher around. They also seem to have a lot of motivation, which partly may come from their circumstances (having a computer available is quite an opportunity for a kid living in an Indian slum), but also must come in part from being able to play and put together knowledge for themselves. The MIT computer clubhouses have success with a similar idea in this country.
At the college level, many schools have advanced undergraduate biology classes where students are given a lab and must pick their own projects and carry them out (though in those cases they get help from biologist-TAs). While we find that giving more guidance than Mitra does is important in our intro-level virtual lab workbooks, students in those smaller classes that are able to use our more advanced, open-ended, self-exploratory labs really like them. So Mitra’s experience with kids in slums seems applicable to college biology as well.
The other point he makes that I think applies pretty broadly, including to our virtual biology labs, is that having students work in groups is often much more powerful for learning than having them work alone. We usually recommend groups of 2 – 3 for our labs. He seems to like groups of 4, though its not clear if he has any data comparing group sizes. All of those group sizes are likely to lead to more learning than groups of one.