Qing-Ke Fu

Papers

Total Citations

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About

Qing-Ke Fu is an emerging scholar in educational technology, whose research focuses on the intersection of robotics, self-regulated learning, and digital competence development. Their most-cited paper, "Emotional supports in robot-based self-regulated learning contexts to promote pre-service teachers’ digital learning resource development competences" (2024), explores how emotionally supportive human-robot interactions can enhance teacher training. This work addresses a critical gap in integrating affective computing with pedagogical design, proposing frameworks that leverage robots as adaptive learning companions. While still early in their career, Fu’s research has garnered attention for its innovative blend of artificial intelligence and education, with the 2024 paper already accumulating 2 citations—a promising start for a recent publication. Their contributions lie in demonstrating how robotic systems can scaffold self-regulated learning processes, particularly for pre-service teachers developing digital resources. By emphasizing emotional support as a key variable, Fu challenges traditional views of robotics in education, advocating for more human-centered approaches. This work holds implications for designing intelligent tutoring systems that respond to learners’ affective states, positioning Fu as a rising voice in the field of technology-enhanced learning.