Hint Generation

Hint generation research focuses on automatically creating helpful guidance for various tasks, primarily leveraging large language models (LLMs) to produce informative hints rather than complete solutions. Current research explores different hint formats (from high-level natural language to specific code examples), investigates the optimal number and sequencing of hints, and examines personalization strategies based on user characteristics and task difficulty. This field is significant for improving human-computer interaction in education, programming assistance, and question answering, ultimately enhancing learning and problem-solving efficiency.