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Robot Learning Companion Offers Custom-tailored Tutoring
March 14, 2016 | NSFEstimated reading time: 4 minutes
Parents want the best for their children's education and often complain about large class sizes and the lack of individual attention.
Goren Gordon, an artificial intelligence researcher from Tel Aviv University who runs the Curiosity Lab there, is no different.
He and his wife spend as much time as they can with their children, but there are still times when their kids are alone or unsupervised. At those times, they'd like their children to have a companion to learn and play with, Gordon says.
That's the case, even if that companion is a robot.
Working in the Personal Robots Group at MIT, led by Cynthia Breazeal, Gordon was part of a team that 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.
Socially assistive robots for education aren't new, but what makes Tega unique is the fact that it can interpret the emotional response of the student it is working with and, based on those cues, create a personalized motivational strategy.
Testing the setup in a preschool classroom, the researchers showed that the system can learn and improve itself in response to the unique characteristics of the students it worked with. It proved to be more effective at increasing students' positive attitude towards the robot and activity than a non-personalized robot assistant.
The team reported its results at the 30th Association for the Advancement of Artificial Intelligence (AAAI) Conference in Phoenix, Arizona, in February.
Tega is the latest in a line of smartphone-based, socially assistive robots developed in the MIT Media Lab. The work is supported by a five-year, $10 million Expeditions in Computing award from the National Science Foundation (NSF), which support long-term, multi-institutional research in areas with the potential for disruptive impact.
The classroom pilot
The researchers piloted the system with 38 students aged three to five in a Boston-area school last year. Each student worked individually with Tega for 15 minutes per session over the course of eight weeks.
A furry, brightly colored robot, Tega was developed specifically to enable long-term interactions with children. It uses an Android device to process movement, perception and thinking and can respond appropriately to children's behaviors.
Unlike previous iterations, Tega is equipped with a second Android phone containing custom software developed by Affectiva Inc. -- an NSF-supported spin-off of Rosalind Picard of MIT -- that can interpret the emotional content of facial expressions, a method known as "affective computing."
The students in the trial learned Spanish vocabulary from a tablet computer loaded with a custom-made learning game. Tega served not as a teacher but as a peer learner, encouraging students, providing hints when necessary and even sharing in students' annoyance or boredom when appropriate.
The system began by mirroring the emotional response of students - getting excited when they were excited, and distracted when the students lost focus - which educational theory suggests is a successful approach. However, it went further and tracked the impact of each of these cues on the student.
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