Children's Expectations, Engagement, and Evaluation of an LLM-enabled Spherical Visualization Platform in the Classroom

This paper presents a classroom study with 9-10 year old Swedish children evaluating an LLM-enabled spherical visualization platform that allows natural language questions about Earth-related datasets with coordinated verbal and visual responses. The study examines children's expectations, engagement patterns, and post-interaction evaluations through structured observation and group discussions in a formal educational setting.

We present our first stage results from deploying an LLM-augmented visualization software in a classroom setting to engage primary school children with earth-related datasets. Motivated by the growing interest in conversational AI as a means to support inquiry-based learning, we investigate children's expectations, engagement, and evaluation of a spoken LLM interface with a shared, immersive visualization system in a formal educational context. Our system integrates a speech-capable large langua

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