Use Algorithms for Adaptive Education

Richard TongRichard Tong is the Chief Architect of Squirrel AI Learning by Yixue Education Group. He is an experienced ed-tech technologist, executive and entrepreneur. He was the Head of Implementation, Greater China Region for Knewton, and Director of Solution Architecture for Amplify Education. He also served as CTO of Phoenix New Media (NYSE:FENG). He has been heavily involved in education technology standardization in the last 8 years. He is a current member of the IEEE AIS (Adaptive Instructional Systems) Standard working group and chair for the 2247.2 Interoperability Subgroup, a member of the IEEE ICICLE (IC Industry Consortium on Learning Engineering) and IEEE FML (Federated Machine Learning) working group. He was a member of the School Interoperability Framework Association (SIFA) Technology Board, and co-chair of the Assessment Group and IDM Group. He also served as a member of the Assessment Interoperability Framework working group for Common Education Data Standard (CEDS), and IMS Global Caliper standard workgroup and Computer Adaptive Testing workgroup, etc.

In this talk, Richard dives into how to use deep learning to enhance BKT, KST, etc. How also looks at how to use SimStudent and Apprentice Learner to build enhanced recommendation policies through reinforcement learning as well as keeping the human-in-the-loop for machine learning. Richard also dives deeper into…

1. Use deep learning to enhance BKT, KST, etc.
2. Use SimStudent and Apprentice Learner to build enhanced recommendation policies through Reinforcement Learning.
3. Keep the human-in-the-loop for machine learning.