Unlocking Student Potential With TA-Bot: Timely Submissions and Improved Code Style
For students learning to write code, developing strong foundational coding skills and cultivating proper code style early on is crucial for success in subsequent courses and professional work. TA-Bot, an automated assessment tool, incorporates novice-friendly style suggestions wrapped around an industry-standard static analysis tool, code correctness testing, and an innovative rate-limiting system called Time Between Submissions ("TBS''). This system works in conjunction with a gamified incentive mechanism designed to motivate students to start weekly assignments earlier. Our hypothesis posited that this incentive, when combined with the inherent effects of TBS, would not only encourage students to initiate assignments sooner but would also prompt them to address more style-related issues and produce higher quality code.
Authors
- Md. Tahmidul Islam Molla (ORCID: https://orcid.org/0000-0003-3414-0717)
- Alexander Gebhard (ORCID: https://orcid.org/0000-0001-7333-3875)
- Dennis Brylow (ORCID: https://orcid.org/0000-0001-5531-3782)
- Jack Forden (ORCID: https://orcid.org/0000-0002-0505-5970)
- Matthew Schneider
Institutions
- Marquette University (US)
- Carnegie Mellon University (US)
Publication Details
- Published
- 2025-02-12
- DOI
- https://doi.org/10.1145/3641554.3701955
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation