Zekun Wu, Man Su, Huiyong Li, Tomohiro Nagashima, Anna Maria Feit — submitted 1 Jul 2026 📄 Full text (arXiv)
Ollie, a gaze-informed AI assistant for children's picture exploration, uses eye-tracking to trigger LLM narrative descriptions; within-subject experiment shows gaze-informed assistance keeps children's attention longer and guides exploration effectively.
Key Contributions
- Ollie, a gaze-informed AI assistant for children's picture exploration, uses eye-tracking to trigger LLM narrative descriptions; within-subject experiment shows gaze-informed assistance keeps children's attention longer and guides exploration effectively.
Connections to AI in Education
This paper contributes to the growing body of research on AI applications in educational settings, specifically in the domains of llm-in-education, intelligent-tutoring-systems, and equity. The findings have implications for how educators design learning experiences that leverage AI while maintaining appropriate pedagogical oversight.
Related Pages
- k-12 — K-12 AI learning tools
- student-experience — student engagement
- adaptive-learning — adaptive learning systems
- intelligent-tutoring-systems — intelligent tutoring systems
Citation
APA: Zekun Wu, Man Su, Huiyong Li, Tomohiro Nagashima, Anna Maria Feit (2026). Gaze-Informed Proactive AI Assistance for Children’s Picture Exploration. arXiv:2607.00445. submitted 1 Jul 2026