Matthew Kenneth Eisenberg

Computer science

Hometown: Gilbert, AZ, United States

Graduation date: Spring 2026

Additional details: Honors student

Data icon, disabled. Four grey bars arranged like a vertical bar chart.

FURI | Spring 2026

Expanding LLM-Assisted Translation of Natural Language to ML-Augmented SQL Queries with Applications in Database Education

This research evaluates large language models (LLMs) as automated graders for SQL assignments in university database courses. Using 139 student submissions, models including Gemini, GPT-4.1-mini, GPT-o4-mini, and Claude are compared against human graders. Through prompt engineering techniques such as rubric integration, few-shot examples, and strictness calibration, model accuracy improved significantly. An ensemble system combining multiple model outputs is being developed to further improve grading consistency and bring automated scores closer to human-level performance.

Mentor:

QR code for the current page

It’s hip to be square.

Students presenting projects at the Fulton Forge Student Research Expo are encouraged to download this personal QR code and include it within your poster. This allows expo attendees to explore more about your project and about you in the future. 

Right click the image to save it to your computer.