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
