Grading Complex Interactive Coding Programs with Reinforcement Learning

This article from Stanford AI explores the application of reinforcement learning to automatically grade interactive coding assignments, drawing parallels to AI's success in mastering games like Atari and Go. The core idea is to treat the grading process as a game where the AI agent interacts with the student's code to determine its correctness and quality. The article highlights the challenges involved in this approach and introduces the "Play to Grade Challenge." The increasing popularity of online coding education platforms like Code.org, with their diverse range of courses, necessitates efficient and scalable grading methods. This research offers a promising avenue for automating the assessment of complex coding assignments, potentially freeing up instructors' time and providing students with more immediate feedback.

• •Reinforcement learning can be applied to automated grading of coding assignments.
• •Treating grading as a game allows AI agents to interact with student code.
• •Online coding education platforms require scalable grading methods.