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.

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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

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article

Unlocking Student Potential With TA-Bot: Timely Submissions and Improved Code Style

Md. Tahmidul Islam Molla, Alexander Gebhard, Dennis Brylow, Jack Forden et al.
AI in Service Interactions
article

Unlocking Student Potential With TA-Bot: Timely Submissions and Improved Code Style

Md. Tahmidul Islam Molla, Alexander Gebhard, Dennis Brylow, Jack Forden, Matthew Schneider
article en

Abstract

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.

Marquette University (US), Carnegie Mellon University (US)
National Science Foundation
Openalex Percentile: Top 99%
AI in Service Interactions
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