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How can we educate the world's population in a scalable, affordable way? This question is driving fascinating research at the intersection of human-computer interaction, social computing, natural language processing, machine learning, and learning sciences. I'll discuss the state-of-the-art in what is becoming known as learning at scale, with a focus on how to improve peer feedback, how to automate grading, and how to help instructors understand what the students understand. I will emphasize how tackling this problem is leading to new socio-technical innovations.
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