Scaling Dialogic Science Communication Training With Large Language Models

This research note explores the potential of artificial intelligence (AI) to support scalable training in science communication. Training scientists in science communication is increasingly being recognized as important, yet existing programs face scalability challenges and often prioritize one-way knowledge dissemination over dialogue. This study explores whether these challenges can be mitigated by integrating AI into the training process. We developed and empirically evaluated DiaLogic – an AI-based communication simulator. In all, 37 students engaged in two simulated dialogues and received AI-generated feedback between sessions. The results showed significant improvements in students’ performance. These findings highlight the promise of AI-based tools to support scalable science communication training.