Introduction: A tinker's guide to learning at scale -- Part I. Three genres of learning at scale: MOOCs and instructor-guided learning -- Algorithm-guided learning: adaptive tutors and computer-assisted instruction -- Peer-guided learning: networked learning communities, aggregators, and syndication -- Testing the genres: learning games -- Part II. Dilemmas in learning at scale: The curse of the familiar -- The edtech Matthew effect -- The trap of routine assessment -- The toxic power of data -- Conclusion: The next robot tutor in the sky.
Summary:
"From MOOCs to autograders to computerized tutors, technologies designed for large-scale learning have never lived up to the hype. Justin Reich once promoted these "transformative" novelties; now he reveals their failures. Successful education reform, he concludes, will focus on incremental institutional change, not the next killer app"-- Provided by publisher.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.