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About

Nazgul Tazhigaliyeva is a researcher at the intersection of human-robot interaction (HRI) and educational technology, with a particular focus on how robots can enhance learning and communication. Her most influential work explores the nuanced roles robots can play in education, especially for children. In her highly cited paper, "Learning with or from the Robot: Exploring Robot Roles in Educational Context with Children" (24 citations), she investigates whether a robot is more effective as a peer co-learner or as a tutor. This line of inquiry is deepened in her second most-cited work, "Should robots win or lose? Robot's losing playing strategy positively affects child learning" (21 citations), which demonstrates a counterintuitive finding: a robot that loses in a game can significantly boost a child’s learning outcomes by modeling the process of learning from failure. Beyond education, Tazhigaliyeva has made notable contributions to accessibility. Her work on the "Cyrillic manual alphabet recognition in RGB and RGB-D data for sign language interpreting robotic system (SLIRS)" (8 citations) and the broader "SLIRS" system (2 citations) aims to develop robotic interpreters for deaf-mute communities, addressing critical communication barriers in public spaces. Her research is characterized by a human-centered approach that leverages robotic imperfection and social dynamics to foster genuine learning and inclusion.