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    <abstract>Grading assessment in data science faces challenges related to scalability, consistency, and fairness. Synthetic dataset and GenAI enable us to simulate realistic code samples and automatically evaluate using rubric-driven systems. The research proposes an automatic grading system for generated Python code samples and explores GenAI grading reliability through human-AI comparison.</abstract>
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%0 Conference Proceedings
%T Automatic Grading of Student Work Using Simulated Rubric-Based Data and GenAI Models
%A Yang, Yiyao
%A Gulbahar, Yasemin
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
%D 2025
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-218-84229-1
%F yang-gulbahar-2025-automatic
%X Grading assessment in data science faces challenges related to scalability, consistency, and fairness. Synthetic dataset and GenAI enable us to simulate realistic code samples and automatically evaluate using rubric-driven systems. The research proposes an automatic grading system for generated Python code samples and explores GenAI grading reliability through human-AI comparison.
%U https://aclanthology.org/2025.aimecon-wip.5/
%P 34-39

Markdown (Informal)

[Automatic Grading of Student Work Using Simulated Rubric-Based Data and GenAI Models](https://aclanthology.org/2025.aimecon-wip.5/) (Yang & Gulbahar, AIME-Con 2025)

• Automatic Grading of Student Work Using Simulated Rubric-Based Data and GenAI Models (Yang & Gulbahar, AIME-Con 2025)

ACL

• Yiyao Yang and Yasemin Gulbahar. 2025. Automatic Grading of Student Work Using Simulated Rubric-Based Data and GenAI Models. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 34–39, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).