Automated Assessment of Students’ Short Written Answers Using NLP and Large Language Models (LLMs)

Assadzadeh, ArianAttia, DemianaGhanta, SanjanaPhan, TaiWalker, Trey2025-06-042025-06-042025-05-09https://hdl.handle.net/10919/135051This project proposes the design and implementation of an automated web-based system for automated formative assessment of student’s short written answer questions using Natural Language Processing (NLP) and Large Language Models (LLMs). The proposed solution addresses the ever-growing challenge in modern education where educators face increasing class sizes, different types of approaches and student abilities, and limited time to give personalized individual feedback for each student. By leveraging recent advances within the area of machine learning, this project’s goal is to offer a scalable, efficient, and meaningful tool that can assist both students and instructors in the feedback process. The tool will feature user authentication, answer uploads, grading via rubric, examples, or concepts, and results displayed in a structured interface like a table.en-USCC0 1.0 UniversalLLMLarge Language ModelsWeb ApplicationAutomationAutomated Short Answers AssessmentASAGEducationPrompt EngineeringAutomated Assessment of Students’ Short Written Answers Using NLP and Large Language Models (LLMs)Article