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About

Susan Bull is a pioneering researcher at the intersection of artificial intelligence, human-computer interaction, and educational technology. Her work focuses on creating intelligent, socially-aware tutoring systems that can adapt to and support learners in deeply personalized ways. A central theme in her research is the development of empathic and robotic tutors that go beyond simple instruction to foster self-regulated learning. Her most influential work, "Towards Empathic Virtual and Robotic Tutors" (2013), has garnered 79 citations, establishing a foundational framework for designing tutors that can perceive and respond to a learner's affective state. Bull has been instrumental in demonstrating how robotic tutors can actively promote metacognitive skills, as shown in her highly-cited 2017 study (49 citations) on helping children plan their own learning paths. She has also advanced the field of Open Learner Modelling (OLM), proving that visualising a learner's own knowledge state through a robot can significantly boost educational outcomes. By integrating social robotics with empathic feedback and transparent models of student knowledge, Bull’s work is shaping the next generation of adaptive, emotionally-intelligent learning companions.