PEER: Empowering Writing with Large Language Models

Abstract

Abstract The emerging research area of large language models (LLMs) has far-reaching implications for various aspects of our daily lives. In education, in particular, LLMs hold enormous potential for enabling personalized learning and equal opportunities for all students. In a traditional classroom environment, students often struggle to develop individual writing skills because the workload of the teachers limits their ability to provide detailed feedback on each student’s essay. To bridge this gap, we have developed a tool called PEER (Paper Evaluation and Empowerment Resource) which exploits the power of LLMs and provides students with comprehensive and engaging feedback on their essays. Our goal is to motivate each student to enhance their writing skills through positive feedback and specific suggestions for improvement. Since its launch in February 2023, PEER has received high levels of interest and demand, resulting in more than 4000 essays uploaded to the platform to date. Moreover, there has been an overwhelming response from teachers who are interested in the project since it has the potential to alleviate their workload by making the task of grading essays less tedious. By collecting a real-world data set incorporating essays of students and feedback from teachers, we will be able to refine and enhance PEER through model fine-tuning in the next steps. Our goal is to leverage LLMs to enhance personalized learning, reduce teacher workload, and ensure that every student has an equal opportunity to excel in writing. The code is available at https://github.com/Kasneci-Lab/AI-assisted-writing .

Topics & Concepts