KOALA: a Configurable Tool for Collecting IDE Data When Solving Programming Tasks
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866916866640838656 |
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| author | Karol, Daniil Artser, Elizaveta Vlasov, Ilya Golubev, Yaroslav Keuning, Hieke Birillo, Anastasiia |
| author_facet | Karol, Daniil Artser, Elizaveta Vlasov, Ilya Golubev, Yaroslav Keuning, Hieke Birillo, Anastasiia |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_21266 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | KOALA: a Configurable Tool for Collecting IDE Data When Solving Programming Tasks Karol, Daniil Artser, Elizaveta Vlasov, Ilya Golubev, Yaroslav Keuning, Hieke Birillo, Anastasiia Software Engineering Computers and Society 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. |
| title | KOALA: a Configurable Tool for Collecting IDE Data When Solving Programming Tasks |
| topic | Software Engineering Computers and Society |
| url | https://arxiv.org/abs/2506.21266 |