Enabling In-Class Peer Feedback on Introductory Computer Science Coding Exercises

Instructors often implement active learning in intro CS courses by giving students in-class coding problems. Students need feedback on their work to improve. While some systems can provide automated feedback, human feedback has been found to be more effective for novice learners. However, it is difficult for instructors to quickly provide feedback at a large scale during coding exercises where time is limited. Peer feedback systems can help students get prompt feedback as well as keep instructors available to address critical problems. Existing peer-feedback systems for computer science usually support feedback on completed code rather than work in progress, so students have less opportunity to reflect on the feedback and correct their work. This thesis introduces a novel system for giving peer feedback on code in progress during introductory CS class sessions. The research work describes the system design, as well as a pilot test of the peer feedback process in summer offerings of CS1. The initial experience in using this tool in a real classroom has implications for the delivery of in-class instruction and for teaching growth mindset in order to take full advantage of peer feedback