preprintApr 19, 2023GREEN OA

Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming

University of Toronto · University of Michigan · +2 more institutions

Indexed inarxivcrossref

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

277
total citations
FWCI
73.13
Percentile
100%
References
96
Citations per year

Authors

6

Topics & keywords

Keywords
  • Computer science
  • Python (programming language)
  • Code (set theory)
  • Scratch
  • Task (project management)
  • Programming language
  • Pair programming
  • Artificial intelligence
UN Sustainable Development Goals
  • Quality Education
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