Directors: Antonio M. Battro and Kurt W. Fischer
Program officer: María Lourdes Majdalani
Challenges and opportunities of emotion-related inspections for child learning applications
With the rapid development of molecular biology, cognitive neuroscience and information science, more and more biochemical and electronic technologies have been developed to inspect the human physiological status, including the emotional status. The learning and education processes are very complex molecular activities and structural remolding processes in the learner’s brain, which should be somewhat revealed by their physiological status and others. It is expected that children learning status could be evaluated through their emotional expressions. Some potential applications for these kind systems could be used in education practices. However, there are limited studies and lack of data in this field until now, since there is no mature and practical systems to use for collecting data from students on the on-line education scene.
In the Research Center of Learning Science, Southeast University, we are trying to develop some practical systems for these studies. Firstly, we are developing the emotional detection system by facial capture and affective computing. We used a set of cameras in the classroom of science education class, took the pictures of the face of the students during the teaching process, and then analyzed and recognized the emotion expressions of each child during the class. We expect that the system can automatically inspect the emotion expressions of each child, and further evaluate the education activities. Secondary, wireless sensor network and wearable computer technology will provide researchers with an advanced and objective research platform for studying learning, which is related to mind, brain and education. We are developing a wireless sensor network system with a few kind of sensors on the body of each child, which can detect in real time and synchronically signals in electrophysiological parameters (such as blood pulse rates, skin temperature, etc.) and behaviors (such as pressure sensors on chairs and body movement by acceleration meter on the body). We are equipping the system in a small classroom and will demonstrate the effectiveness of this kind sensor system for the child emotion detection. Finally, we are also building platform for low-cost, rapid and easy detection systems for determining emotion-related gene types (DNAs from nonnasality severed cells) and detecting various emotion-related neurotransmitter (such as cortisones from saliva) or hormones. The detection might help the teachers to find the stress of children during the class or school, and the degree of sensitivity when one child faces the stress. All the systems and the related experiments are still undergoing in RCLS. We believe that combination of several different platforms to synchronically obtain signals various data of electrophysiological signals, facial expression, behavior expressions and molecular markers together will give some useful information about child’s learning and evaluate the education effectiveness for different children.