Using Fine-tuned LLMs to Grade Homework
Location
Gold Coast I/II
Start Date
28-5-2025 4:00 PM
End Date
18-5-2025 4:25 PM
Description
LLMs have the potential to improve education by automatically grading homework and giving students hints. However, due to hallucinations and general lack of capabilities, using LLM for grading and giving hints has mixed results. The performance of LLMs can be improved by using methods such as prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning. In this talk, we explore the possibility of using fine-tuned LLMs to grade and give hints. Fine-tuning an LLM allows one to take a pretrained LLM, such as those built by OpenAI, and adapt the LLM for a highly specific purpose.
Recommended Citation
Bohacek, Stephan, "Using Fine-tuned LLMs to Grade Homework" (2025). Teaching and Learning with AI Conference Presentations. 61.
https://stars.library.ucf.edu/teachwithai/2025/wednesday/61
Using Fine-tuned LLMs to Grade Homework
Gold Coast I/II
LLMs have the potential to improve education by automatically grading homework and giving students hints. However, due to hallucinations and general lack of capabilities, using LLM for grading and giving hints has mixed results. The performance of LLMs can be improved by using methods such as prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning. In this talk, we explore the possibility of using fine-tuned LLMs to grade and give hints. Fine-tuning an LLM allows one to take a pretrained LLM, such as those built by OpenAI, and adapt the LLM for a highly specific purpose.