Exploring a Robot Companion to Encourage Resilience in Mathematics: Initial Research Study
In an ongoing study, researchers are expanding the data collected from parent-child math problem-solving interactions to better understand the role of a robotic companion in fostering mathematical perseverance in children. The ultimate goal is to design a robot that can partner with teachers in busy classrooms, providing adaptive, emotionally-aware support to sustain student motivation and engagement.
Initial findings from the study emphasize the importance of trust and balanced social behaviour in robots. Affect-sensitive social robots can respond to students' emotional states and scaffold challenges in real time, complementing the teacher’s efforts without overwhelming the interaction.
The design of such robotic companions focuses on multimodal communication strategies, combining verbal and nonverbal cues, adaptive social behaviour, and emotional expressiveness to build trust and engagement among students. The key is to calibrate the robot’s responses effectively, ensuring they support learning without distracting or frustrating students.
These robots promote perseverance by encouraging students to persist through difficult math problems, adapting their assistance based on students' observable affect (e.g., frustration or confidence). Preliminary research suggests that affect-sensitive robots could boost perseverance in mathematics by making challenges feel more manageable and providing timely, empathetic motivational support.
In practice, these robots serve as companions who engage students in problem-solving tasks, providing prompts and encouragement aligned with constructionist approaches to learning that emphasise active engagement and resilience. Initial research with Arduino robotics projects shows that integrating hands-on, robot-supported learning enhances task persistence, indicating that affect-sensitive robots could have a similar impact on mathematics.
The study involves multiple parent-child pairs, with additional data elements, and the collection of a multi-modal dataset from a child solving math problems coached by a parent tutor. The research is focused on understanding the role of a robotic companion in cultivating mathematical perseverance in children.
Overall, the design and deployment of affect-sensitive social robots in classrooms aim to complement teachers by managing individual motivation and persistence, particularly when classroom constraints limit personalised attention. Key design principles include trustworthiness, emotional sensitivity, and adaptable social interaction calibrated to support learning and perseverance without causing distraction or disengagement.
Artificial-intelligence-powered robots, designed for education-and-self-development, could potentially use technology to provide adaptive, empathetic support to students in math problem-solving, helping them learn by encouraging persistence and managing motivation. By combining multimodal communication strategies, these robots aim to foster a sense of trust, engagement, and perseverance among students, ultimately enhancing their learning experience.
