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MIT Better World

PRG is working toward a future in which, simply put, we “live better with robots.” Its award-winning creations Nexi and Leonardo, for example, are designed to fit engagingly into peer-to-peer teamwork and family life. “Over the past few years,” Breazeal says, “our research has focused on advancing the artificial intelligence, user experience design, and application of social robots in the real world where they help people achieve long-term goals and can build personalized and positive relationships.” Educational goals are of particular interest: “There is huge need to help children enter school ready to learn, and social robots can offer something truly unique as an intervention both in schools and homes.”

Enter Tega, the product of extensive research on child-robot interaction and educational best practices. The development of Tega was led by former graduate student Jin Joo Lee SM ’11, PhD ’17, along with numerous contributors who designed and assembled early prototypes. Research scientist Hae Won Park has spearheaded the interaction intelligence and deployment of Tega out in the field—most recently on a three-month literacy study in Massachusetts kindergartens, meeting weekly with children from 12 different classrooms. Tega is equipped to tell stories to kids, then to conduct autonomous conversations about those stories, testing comprehension and vocabulary and making emotional or inferential prompts (“how did the frog feel?” or “what will happen next?”)—all while tailoring its hints and reactions to the child’s verbal and physical responses. Eventually, Tega invites the child to retell the story. “By analyzing the story and speech sample, Tega can gauge that child’s language ability and which parts of a story the child is particularly interested in,” says Park. Relationship-building moments—such as conversations in which both child and robot share what they like about school—are key to nurturing richer, more personalized repeat interactions.

Degrees of freedom: these five movements combine to give Tega its range of physical expression.

Tega’s bubbly, childlike demeanor makes it a unique research tool as well as educational platform. “As human beings, we are wired to learn from others,” Breazeal observes. And because it is designed to interact with kids as a peer rather than a tutor and to model productive mindsets, Tega offers a powerful, flexible social learning dynamic that PRG is doing rigorous experiments to better understand. Findings so far have reinforced the idea that “we learn not just knowledge and skills from others, but also important attitudes about learning—such as to be open and curious, to persevere through challenge, and to see mistakes as an opportunity to learn and grow.”

Robot Design, Assembly, and Development: Version 1: Jin Joo Lee SM ’11, PhD ’17, Luke Plummer ’14, Kristopher dos Santos ’10, SM ’12, Sigurður örn Aðalgeirsson, Cooper Perkins Inc., IFRobots Inc., Stacey Dyer, Fardad Faridi. Version 2: Hae Won Park, Meng Xi, Randi Williams, Cooper Perkins Inc.

Advisors on Classroom Interactions and Data Analysis: David DeSteno, Northeastern University; Paul Harris, Harvard University; Stephanie Gottwald, Curious Learning; Maryanne Wolf, Stanford University