Exploring EEG-based Attention Levels in Human-AI Interactions: A Case Study

This study used a non-invasive electroencephalogram (EEG) instrument to explore learner attention during interactions with AI chatbots. Compared with traditional self-reported surveys, EEG-based data offer a more direct and objective method for measuring cognitive engagement. To assess differences in attention levels before and after interacting with AI chatbots, the authors invited three Chinese college students to participate in this case study. The results indicated their attention levels increased during chatbot interactions, suggesting that personalized and interactive AI tools can help students stay focused. This case study contributes to the literature on observing cognitive engagement and offers educators a fresh strategy for improving students’ attention and academic performance.