CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs
University of Toronto · Microsoft (United States) · +1 more institution
Abstract
Timely, personalized feedback is essential for students learning programming. LLM-powered tools like ChatGPT offer instant support, but reveal direct answers with code, which may hinder deep conceptual engagement. We developed CodeAid, an LLM-powered programming assistant delivering helpful, technically correct responses, without revealing code solutions. CodeAid answers conceptual questions, generates pseudo-code with line-by-line explanations, and annotates student’s incorrect code with fix suggestions. We deployed CodeAid in a programming class of 700 students for a 12-week semester. A thematic analysis of 8,000 usages of CodeAid was performed, further enriched by weekly surveys, and 22 student interviews.…
Citation impact
- FWCI
- 76.15
- Percentile
- 100%
- References
- 52
Authors
7Topics & keywords
- Computer science
- Code (set theory)
- Software deployment
- Transparency (behavior)
- Thematic analysis
- Class (philosophy)
- Multimedia
- Software engineering
- Quality Education