Inclusive Citizen Science: Engaging Visually Impaired Students with Chatbots

Citizen science initiatives depend on the participation of large numbers of volunteers. However, many projects fail to adopt inclusive design strategies. This can limit accessibility for individuals with disabilities, particularly those with visual impairments. Here, we present a transformation of a visual-based citizen science task into a conversational chatbot interface enhanced with data sonification. The system is specifically designed to empower visually impaired children and teenagers for scientific participation. It leverages natural language processing and human-computer interaction to enable dialogue-based interactions, providing access to meteor-echo data without reliance on visual interfaces. The Sky Sounds project served as the study context, where 57 visually impaired children and teenagers classified meteor sounds through this accessible interface. The results revealed high engagement and satisfaction across all groups, demonstrating that the combination of conversational interaction and auditory representations can effectively support non-visual scientific classification tasks. These findings highlight the potential of conversational artificial intelligence combined with auditory interfaces to reduce participation barriers and foster inclusive practices in science education. Our approach is highly adaptable and scalable, offering a blueprint for extending accessibility to other citizen science domains.