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© 2020 Elsevier Ltd 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 he/she knows. While both agent-role paradigms have been shown to promote student learning, we hypothesize that there will be heightened benefit with respect to students’ learning and emotional engagement if the agent engages children in a more peer-like way — adaptively switching between tutor/tutee roles. In this work, we present a novel active role-switching (ARS) policy trained using reinforcement learning, in which the agent is rewarded for adapting its tutor or tutee behavior to the child's knowledge mastery level. To investigate how the three different child–agent interaction paradigms (tutee, tutor, and peer agents) impact children's learning and affective engagement, we designed a randomized controlled between-subject experiment. Fifty-nine children aged 5–7 years old from a local public school participated in a collaborative word-learning activity with one of the three agent-role paradigms. Our analysis revealed that children's vocabulary acquisition benefited from the robot tutor's 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 peer-like agent brought the most benefit to children's 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 (tutor/tutee) and adaptive role (peer) agents support children's cognitive and emotional needs as they play and learn. It also contributes to an important new dimension of designing educational agents — actively adapting roles based on the student's engagement and learning needs.