Teaching and learning with children: Impact of reciprocal peer learning with a social robot on childrenxe2x80x99s learning and emotive engagement Abstract   Pedagogical agents are typically designed to take on a single role: either as a tutor who guides and instructs the student, or as a tutee that learns from the student to reinforce what heshe knows. While both agentrole paradigms have been shown to promote student learning, we hypothesize that there will be heightened benefit with respect to studentsxe2x80x99 learning and emotional engagement if the agent engages children in a more peerlike way xe2x80x94 adaptively switching between tutortutee roles. In this work, we present a novel active roleswitching (ARS) policy trained using reinforcement learning, in which the agent is rewarded for adapting its tutor or tutee behavior to the childxe2x80x99s knowledge mastery level. To investigate how the three different childxe2x80x93agent interaction paradigms (tutee, tutor, and peer agents) impact childrenxe2x80x99s learning and affective engagement, we designed a randomized controlled betweensubject experiment. Fiftynine children aged 5xe2x80x937 years old from a local public school participated in a collaborative wordlearning activity with one of the three agentrole paradigms. Our analysis revealed that childrenxe2x80x99s vocabulary acquisition benefited from the robot tutorxe2x80x99s instruction and knowledge demonstration, whereas children exhibited slightly greater affect on their faces when the robot behaves as a tutee of the child. This synergistic effect between tutor and tutee roles suggests why our adaptive peerlike agent brought the most benefit to childrenxe2x80x99s vocabulary learning and affective engagement, as compared to an agent that interacts only as a tutor or tutee for the child. This work sheds light on how fixed role (tutortutee) and adaptive role (peer) agents support childrenxe2x80x99s cognitive and emotional needs as they play and learn. It also contributes to an important new dimension of designing educational agents xe2x80x94 actively adapting roles based on the studentxe2x80x99s engagement and learning needs.

Preschoolersxe2x80x99 Understanding of a Teachable AgentBased Game in Early Mathematics as Reflected in their Gaze Behaviors xe2x80x93 an Experimental Study This study investigated how preschool children processed and understood critical information in Magical Garden, a teachable agentbased playu0026learn game targeting early math. We analyzed 36 childrenxe2x80x99s (ages 4xe2x80x936xc2xa0years) realtime behavior during gameuse to explore whether children: (i) processed the information meant to support number sense development; (ii) showed an understanding of the teachable agent as an entity with agency. An important methodological goal was to go beyond observable behavior and shed some light on how cognitive processing and understanding in children of such young age can be studied. First, the children played Magical Garden for three weeks to get acquainted with the game. Second, in an experimental part of the study, the childrenxe2x80x99s gaze behaviors were measured during 5 rounds of interaction with an experimental version of one of the subgames. The analyses suggest that two of the gaze behaviors were positively correlated with the game performance measure, as hypothesized. Another result was that children looked at the teachable agent significantly more often when the teachable agent had been in charge of gameplay than when it had not. This can be interpreted as an indication that the children had an understanding of their teachable agent as an entity that, like themselves and unlike other dynamic visual elements in the game, made decisions based on own xe2x80x98knowledgexe2x80x99. In a broader context, the findings are important in showing the potential gains of combining log data with eyetracking data for developing and refining AI algorithms for adaptive individual feedback and scaffolding.