- Abstract
- Learning to write high-quality code is a critical skill for novice programmers, but manual code reviews are resource-intensive and do not scale well. Existing automated tools may fail to provide feedback that is relevant to novices, and even many educational tools overlook some novice-specific code quality defects or are difficult to adapt to new settings. To address these limitations, we developed EduLint, a customizable educational linter. It detects a wide range of novice-specific defects – many of which are not addressed by other tools – and is easy to adapt to diverse educational settings. To demonstrate this, we describe its deployments in several different courses and seminars, including a large CS1 course where students were required to fix issues EduLint identified. In a quasiexperiment, we observed that students were better at avoiding some of the defects several months after the CS1 course ended. Students also rated EduLint as clear and easy to use. Across all the deployments, EduLint has already delivered code quality feedback on hundreds of thousands of defects to thousands of users.
- When: Thu 19 Feb 2025 14:00 - 14:20 at Meeting Room 105 - AI-Enhanced Tools, Training, and Equity in Computing Education
- Time and location are preliminary and subject to change
- Paper – ACM DL, PDF
- Presentation – Google Slides
- EduLint documentation and User Guides
- try-it-yourself example
- Authors
- Contact
- Catch me during the conference
- Message me at: anna.rechtackova@mail.muni.cz