A team of researchers from the Massachusetts Institute of Technology (MIT) is working on a new social robot that is helping students learn through personalized interactions. A team led by Cynthia Breazeal, director of the Personal Robots Group at the MIT Media Laboratory, developed a socially assistive robot called “Tega” that is designed to serve as a one-on-one peer learner in or outside of the classroom. Also Read - Volkswagen charging robot will find and charge your Electric Vehicle; Here is how it would workAlso Read - Hackers can remotely control robots left unsecured on internet: Study
“Tega”, the latest in a line of smartphone-based, socially assistive robots developed in the MIT Media Lab, is unique as it can interpret the emotional response of the student it is working with and, based on those cues, create a personalized motivational strategy. “We started with a very high-quality approach, and what is amazing is that we were able to show that we could do even better,” said Goren Gordon, an artificial intelligence (AI) researcher from Tel Aviv University in Israel.
After testing the set-up in a pre-school classroom, the team showed that the system can learn and improve itself in response to the unique characteristics of the students it worked with. The results, shared at the 30th Association for the Advancement of Artificial Intelligence (AAAI) Conference in Phoenix, Arizona, recently, proved the machine to be more effective at increasing students’ positive attitude towards the robot and activity than a non-personalized robot assistant.
Specifically developed to enable long-term interactions with children, “Tega” uses an Android device to process movement, perception and thinking and can respond appropriately to children’s behaviors. The robot is equipped with an Android phone containing customised software that can interpret the emotional content of facial expressions, a method known as “affective computing.”
“What is so fascinating is that children appear to interact with Tega as a peer-like companion in a way that opens up new opportunities to develop next-generation learning technologies that not only address the cognitive aspects of learning, like learning vocabulary but the social and affective aspects of learning as well,” Breazeal said.