AnnotateGPT: Designing Human-AI Collaboration in Pen-Based Document Annotation

Providing high-quality feedback on writing is cognitively demanding, requiring reviewers to identify issues, suggest fixes, and ensure consistency. We introduce AnnotateGPT, a system that uses pen-based annotations as an input modality for AI agents to assist with essay feedback. AnnotateGPT enhances feedback by interpreting handwritten annotations and extending them throughout the document. One AI agent classifies the purpose of each annotation, which is confirmed or corrected by the user. A second AI agent uses the confirmed purpose to generate contextually relevant feedback for other parts of the essay. In a study with 12 novice teachers annotating essays, we compared AnnotateGPT with a baseline pen-based tool without AI support. Our findings demonstrate how reviewers used annotations to regulate AI feedback generation, refine AI suggestions, and incorporate AI-generated feedback into their review process. We highlight design implications for AI-augmented feedback systems, including balanced human-AI collaboration and using pen annotations as subtle interaction.