Human learning is a complex interactive and iterative process that takes place at a very finegrained level. However, our ability to understand this fascinating latent learning process is often limited by what we can perceive and how we can measure. Recent advances of sensing technology and accompanying techniques for processing multimodal data, which manifest the
psychological as well physiological processes during the human learning process, give us a new opportunity to look at this classical problem with a new pair of lens. The emerging new type of data includes, but not limited to, student’s physiological signals such as EKG or EEG waveforms, students’ speech, facial expressions and postures, within the context of particular learning activities. We are particularly interested in those data gathered from the real-world educational activities versus those from the controlled lab environment.