KOALA: a Configurable Tool for Collecting IDE Data When Solving Programming Tasks
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Abstract (arXiv)
Collecting data of students solving programming tasks is incredibly valuable for researchers and educators. It allows verifying that the students correctly apply the features and concepts they are taught, or finding students' misconceptions. However, existing data collection tools have limitations, e.g., no control over the granularity of the collected code, not collecting the specific events of the programming environment used, and overall being hard to configure. To overcome these limitations, we propose KOALA, a convenient and highly configurable tool for collecting code snapshots and feature usage from students solving programming tasks in JetBrains IDEs. The plugin can be installed in IDEs and configured to provide the students with the necessary tasks, enable or disable certain IDE features like code completion, and run surveys. During problem solving, the plugin collects code snapshots at the configured granularity, all IDE actions like running and debugging, as well as some data not collected in prior works, like employed hotkeys and switching focus between files. The collected data is sent to the server that comes with the tool, where it is stored and can be converted to the standardized ProgSnap2 format. To showcase the tool, we collected data from 28 students solving tasks in two courses within the IDE, highlighting some insights from this data.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Jun 2025.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2026RECAP: An End-to-End Platform for Capturing, Replaying, and Analyzing AI-Assisted Programming Interactionscited by 1
- 2025Understanding Student Interaction with AI-Powered Next-Step Hints: Strategies and Challengescited by 0
- 2026To Tab or Not to Tab: Measuring Critical Engagement in AI Code Completion Tools Using Behavioral Signals and Attention Checkscited by 0
- 2026To Tab or Not to Tab: Measuring Critical Engagement in AI Code Completion Tools Using Behavioral Signals and Attention Checks29 Jun 2026
- 2026RECAP: An End-to-End Platform for Capturing, Replaying, and Analyzing AI-Assisted Programming Interactions1 May 2026
- 2025Understanding Student Interaction with AI-Powered Next-Step Hints: Strategies and Challenges9 Nov 2025