A 21st Century Model for Disseminating Knowledge
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Abstract — In the early years of the third millenium, most professors are still teaching in virtually the same way they were taught and their teachers were taught, stretching back centuries. This situation is likely to change, relatively soon. Technology is transforming (if not threatening to overwhelm) higher education, as MOOCs and online content become widely available. University students seeking to learn a topic who now have little if any choice are about to be presented with a vast array of choices. What student would not want to swap a tired professor writing slowly on a chalkboard for a well-produced series of videos and associated content, given by a world leader in the field? We are on the verge of a transformation on the scale of the transformation wrought by Gutenburg. This imminent change raises a host of fascinating and far-reaching questions.
In this talk, we describe a scalable model for teaching and learning based on a combination of studio-produced video lectures, innovative online content and assessment mechanisms, and an authoritative classic textbook. We initially proved this approach effective for teaching algorithms and data structures, the analysis of algorithms, and analytic combinatorics. More recently, we have published a new textbook in computer science, new studio-produced lectures, and online content that teachers and learners can use for a first-year course sequence in computer science that can stand alongside traditional first courses in physics, chemistry, economics, and other disciplines. Our model now enables us to reach millions of students and professionals around the world.
Biography — Robert Sedgewick is the founding chair and the William O. Baker Professor in the Department of Computer Science at Princeton and served for many years as a member of the board of directors of Adobe Systems. He has held visiting research positions at Xerox PARC, IDA, INRIA, and Bell Laboratories.
Prof. Sedgewick’s research interests include analytic combinatorics, algorithm design, the scientific analysis of algorithms, and innovations in the dissemination of knowledge. He has published widely in these areas and is the author of twenty books, which have sold nearly one million copies. He has also published extensive online content (including studio-produced video lectures) on analysis of algorithms and analytic combinatorics and (with Kevin Wayne) algorithms and computer science. Their MOOC on algorithms has been named one of the “top 10 MOOCs of all time.”