Madina Karasheva
Papers
1
Total Citations
2
H-Index
1
About
Driven by a passion for human-robot interaction and educational technology, Madina Karasheva’s research centers on robot-assisted language learning (RALL) and collaborative learning paradigms. Her most cited work, “Language Learning using Caption Generation within Reciprocal Multi-Party Child-Tutor-Tutee Interaction” (2023, 2 citations), pioneers the integration of reciprocal peer tutoring (RPT) with automated caption generation to enhance speaking skills in children. Karasheva’s key contribution lies in designing multi-party interaction frameworks where robots dynamically alternate between tutor and tutee roles, fostering deeper engagement and linguistic output. This approach addresses a critical gap in RALL by moving beyond one-on-one robot-child dialogues to more natural, collaborative exchanges. Her work has been recognized for its potential to scale personalized language support, particularly for young learners. Though early in her career, Karasheva’s innovative fusion of peer tutoring principles with AI-driven captioning positions her as a rising voice in educational robotics, with implications for both classroom practice and human-robot collaboration design.
Research Focus
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Top Papers
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