Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
University of Toronto · University of Michigan · +2 more institutions
Abstract
AI code generators like OpenAI Codex have the potential to assist novice programmers by generating code from natural language descriptions, however, over-reliance might negatively impact learning and retention. To explore the implications that AI code generators have on introductory programming, we conducted a controlled experiment with 69 novices (ages 10-17). Learners worked on 45 Python code-authoring tasks, for which half of the learners had access to Codex, each followed by a code-modification task. Our results show that using Codex significantly increased code-authoring performance (1.15x increased completion rate and 1.8x higher scores) while not decreasing performance on manual code-modification tasks.…
Citation impact
- FWCI
- 73.13
- Percentile
- 100%
- References
- 96
Authors
6Topics & keywords
- Computer science
- Python (programming language)
- Code (set theory)
- Scratch
- Task (project management)
- Programming language
- Pair programming
- Artificial intelligence
- Quality Education