RoboBuddy in the Classroom: Exploring LLM-Powered Social Robots for Storytelling in Learning and Integration Activities
This addresses the problem of reducing planning time for teachers using social robots in multicultural integration and learning activities, though it is incremental as it builds on existing technologies.
The researchers tackled the time-intensive planning of scenario-based educational activities, especially with social robots, by implementing an intuitive interface using LLMs and social robots to create such activities from regular curriculum. They co-designed frameworks with 4 teachers and deployed it in a week-long study with 27 students, finding significantly higher student enjoyment with storytelling and positive impacts on integration policies.
Creating and improvising scenarios for content approaching is an enriching technique in education. However, it comes with a significant increase in the time spent on its planning, which intensifies when using complex technologies, such as social robots. Furthermore, addressing multicultural integration is commonly embedded in regular activities due to the already tight curriculum. Addressing these issues with a single solution, we implemented an intuitive interface that allows teachers to create scenario-based activities from their regular curriculum using LLMs and social robots. We co-designed different frameworks of activities with 4 teachers and deployed it in a study with 27 students for 1 week. Beyond validating the system's efficacy, our findings highlight the positive impact of integration policies perceived by the children and demonstrate the importance of scenario-based activities in students' enjoyment, observed to be significantly higher when applying storytelling. Additionally, several implications of using LLMs and social robots in long-term classroom activities are discussed.