NeuroChat: A Neuroadaptive AI Chatbot for Customizing Learning Experiences
Journal:
arXiv
Published Date:
Mar 10, 2025
Abstract
Generative AI is transforming education by enabling personalized, on-demand
learning experiences. However, AI tutors lack the ability to assess a learner's
cognitive state in real time, limiting their adaptability. Meanwhile,
electroencephalography (EEG)-based neuroadaptive systems have successfully
enhanced engagement by dynamically adjusting learning content. This paper
presents NeuroChat, a proof-of-concept neuroadaptive AI tutor that integrates
real-time EEG-based engagement tracking with generative AI. NeuroChat
continuously monitors a learner's cognitive engagement and dynamically adjusts
content complexity, response style, and pacing using a closed-loop system. We
evaluate this approach in a pilot study (n=24), comparing NeuroChat to a
standard LLM-based chatbot. Results indicate that NeuroChat enhances cognitive
and subjective engagement but does not show an immediate effect on learning
outcomes. These findings demonstrate the feasibility of real-time cognitive
feedback in LLMs, highlighting new directions for adaptive learning, AI
tutoring, and human-AI interaction.
