Using Generative AI and Multi-Agents to Provide Automatic Feedback

Understand

This study investigates the use of generative AI and multi-agent systems to provide automatic feedback in educational contexts, particularly for student constructed responses in science assessments.

• The research addresses a key gap in the field by exploring how multi-agent systems, called AutoFeedback, can improve the quality of GenAI-generated feedback, overcoming known issues such as over-praise and over-inference that are common in single-agent large language models (LLMs).
• The study developed a multi-agent system consisting of two AI agents: one for generating feedback and another for validating and refining it.
• The system was tested on a dataset of 240 student responses, and its performance was compared to that of a single-agent LLM.