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Machine-Guided Learning Matches Teachers In Study
New submitter dougled writes "A study at six universities found that students taught statistics mainly through software learned as much as peers taught primarily by humans. And the robots got the job done more quickly. '... our results indicate that hybrid-format students took about one-quarter less time to achieve essentially the same learning outcomes as traditional-format students.' They add, 'There is every reason to expect these systems to improve over time, perhaps dramatically, and thus it is not foolish to believe that learning outcomes will also improve.'"
Was the teacher tutoring a single student, as the machine was? How does the machine do when teaching a group of 30? I suspect that all we have really learned is that individual tutoring is better for some topics.
Of course computers can be less expensive tutors so the approach does have merit.
By offloading the rote and basic informational dispersal to the students, that would hopefully free up the teacher to focus on walking through real demonstrations and examples, interacting with students, and helping out with some of the difficult-to-understand areas, instead of spending most of their time doing the same lecture-style material over and over.
A teacher can understand what essential part of understanding you are missing and make an analogy that explains exactly that. He can then change the analogy if you don't get it. This, of course, assumes rather few students per teacher, and good teachers. But by all means, let's find out where humans do well and where computers are better.
At the university where I work, the experience seems to be that class discussions work better in e-learning courses. This could be because even quiet types will join in, or because people spend longer time thinking about their answers. This is, of course, only anecdotal.