Emelie Jin

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About

Emelie Jin is a leading researcher at the intersection of human-robot interaction and second language acquisition. Her work centers on designing and evaluating robot-led conversation practice for L2 learners, with a particular focus on integrating human-like spoken and non-verbal interaction strategies to enhance learning outcomes. In her most-cited study, "Learner and teacher perspectives on robot-led L2 conversation practice" (2022, 11 citations), Jin conducted semi-structured interviews with both learners and teachers to derive actionable recommendations for more natural and effective robot-mediated dialogue. This research bridges a critical gap between user expectations and technological design, offering evidence-based guidelines for building socially adept educational robots. Beyond this foundational paper, Jin’s broader contributions include advancing our understanding of how non-verbal cues—such as gesture and gaze—can be programmed into robots to foster engagement and reduce anxiety in language learners. Her work has been recognized for its practical impact, directly informing the development of conversational agents used in classrooms and self-study tools. By centering the voices of end-users, Jin continues to shape a future where robots serve as patient, adaptive partners in language education.