AI for improving teaching and learning

We haven't figured out how to make the perfect robot tutors. But we have figured out how make them much more effective in improving student learning outcomes with modern AI techniques. Varun Arora covers some of those important techniques, along with real-world examples.

AI has long been treated with disdain by the education community because of its potential to replace teachers with robots. This rhetoric is widely spread even while the country faces one of the most acute K–12 teacher shortages and largest inequalities in achievement in the history of time. Instead of a world where teachers are replaced with AI-powered intelligent tutor systems (ITSs) and MOOCs, Varun Arora presents an alternative future, one where teachers are the solution and AI is an important tool in their arsenal. Varun shares some of the recent successes in deep learning, reinforcement learning, and knowledge representation and extraction in the context of the most complex teaching and learning challenges in K–12 and higher education today. Varun also dives into some of the more unique challenges faced when building models in the educational domain, particularly as they relate to significant training data, privacy, and lowering bias, and highlights applications of pattern recognition AI solutions in classrooms today, along with data on their effectiveness. Varun concludes by exploring open challenges in the teaching and learning domains, the state of current research, and areas for most impact in education and economy upskilling in America today.