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ACTIVE-ating Artificial Intelligence: Integrating Active Learning in an Introductory Course

AI Magazine

Column n The Educational Advances in Artificial Intelligence column discusses and shares innovative educational approaches that teach or leverage AI and its many subfields at all levels of education (K-12, undergraduate, and graduate levels). By restructuring the course into a format that was roughly half lecture and half small-group problem solving, I was able to significantly increase student engagement, their understanding and retention of difficult concepts, and my own enjoyment in teaching the class. The ACTIVE Center's design was based on research on the power of collaborative learning to promote student success and retention, particularly for women, underrepresented minorities, and transfer students, who benefit greatly from building stronger connections with their peers through shared active learning experiences (Zhao, Carini, and Kuh 2006; Rypisi, Malcolm, and Kim 2009; Kahveci, Southerland, and Gilmer 2006). The ACTIVE Center, a 40-student classroom, includes movable furniture (20 trapezoidal tables and 40 lightweight rolling chairs) that is typically grouped into 10 hexagonal table clusters but that can also be arranged into lecture-style rows, a boardroom or seminar-style rectangular layout, or individual pair-activity tables. The room also has an Epson Brightlink "smart projector" at the front of the room, four flat-panel displays (which can be driven centrally by the instructor's laptop or individually through HDMI ports), and 10 rolling 4 x 6 foot whiteboards for use during group problem-solving activities, as well as smaller, portable tabletop whiteboards.


These graduate students had no idea their teaching assistant was a robot

#artificialintelligence

On the Internet, "nobody knows you're a dog," as the old meme goes, and today, the same can increasingly be said of robots. There are already scheduling robots that are virtually indistinguishable from humans, and recently students at the Georgia Institute of Technology learned that "Jill Watson" -- a teaching assistant they had relied upon all semester -- was in fact artificially intelligent. "The world is full of online classes, and they're plagued with low retention rates," said Ashok Goel, a Georgia Tech professor who teaches a class entitled Knowledge-Based Artificial Intelligence. "One of the main reasons many students drop out is because they don't receive enough teaching support. We created Jill as a way to provide faster answers and feedback."


An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods

Zhang, Tong

AI Magazine

This book is an introduction to support vector machines and related kernel methods in supervised learning, whose task is to estimate an input-output functional relationship from a training set of examples. A learning problem is referred to as classification if its output take discrete values in a set of possible categories and regression if it has continuous real-valued output.