We believe that machines can help humans teach and learn better. That is why we combine artificial intelligence and machine learning with insights from the learning sciences to better understand what people know and how they learn.
The CHILI lab (Computer-Human Interaction in Learning and Instruction) follows two approaches: developing new learning technologies that produce novel sources of data on how people teach and learn, and using machine learning and statistical methods to unlock the insights that are hidden in these sources of data.
CHILI develops novel technologies designed to support teaching and learning, with a focus on learning in team settings. Many of the technologies created provide the ability to capture novel sources of data on how individuals teach and learn together. In addition to traditional statistical methods, the use of Learning Analytics helps making sense of the data.
By using state-of-the-art methods from machine learning and artificial intelligence, CHILI uncovers insights about how people teach, how people learn, and how technologies are best able to support teaching and learning. These methods have helped us understand the learning process across a wide variety of educational settings and with a variety of different technologies, including with educational robotics, in online learning environments, and when using tangible user interfaces.