# Empirical Study of Large Language Models as Automated Essay Scoring Tools in English Composition__Taking TOEFL Independent Writing Task for Example

arXiv: https://arxiv.org/abs/2401.03401 · HTML: https://mlsanity.com/paper/2401.03401/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 35 references that are in the map.
- First posted on arXiv 7 Jan 2024.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Deep contextualized word representations](https://mlsanity.com/paper/1802.05365/) (2018)
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://mlsanity.com/paper/2107.13586/) (2021)
- [Making Pre-trained Language Models Better Few-shot Learners](https://mlsanity.com/paper/2012.15723/) (2020)
- [AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://mlsanity.com/paper/2304.06364/) (2023)
- [Chain of Hindsight Aligns Language Models with Feedback](https://mlsanity.com/paper/2302.02676/) (2023)
- [Automatic Text Scoring Using Neural Networks](https://mlsanity.com/paper/1606.04289/) (2016)
- [Matching Exemplar as Next Sentence Prediction (MeNSP): Zero-shot Prompt Learning for Automatic Scoring in Science Education](https://mlsanity.com/paper/2301.08771/) (2023)
- [Cognitively Aided Zero-Shot Automatic Essay Grading](https://mlsanity.com/paper/2102.11258/) (2021)

## Built on by (most cited first, 8 of 8)

- [Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course](https://mlsanity.com/paper/2407.05216/) (2024)
- [Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoring](https://mlsanity.com/paper/2407.18328/) (2024)
- [EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Models](https://mlsanity.com/paper/2502.11916/) (2025)
- [CAFES: A Collaborative Multi-Agent Framework for Multi-Granular Multimodal Essay Scoring](https://mlsanity.com/paper/2505.13965/) (2025)
- [Agreement Between Large Language Models and Human Raters in Essay Scoring: A Research Synthesis](https://mlsanity.com/paper/2512.14561/) (2025)
- [From Test-taking to Cognitive Scaffolding: A Pedagogical Diagnostic Benchmark for LLMs on English Standardized Tests](https://mlsanity.com/paper/2505.17056/) (2025)
- [Decision-Level Ordinal Modeling for Multimodal Essay Scoring with Large Language Models](https://mlsanity.com/paper/2603.14891/) (2026)
- [Machine--human agreement in marking undergraduate assignments is specific to model, prompt and institution](https://mlsanity.com/paper/2610.18019/) (2026)

## Abstract (arXiv)

Large language models have demonstrated exceptional capabilities in tasks involving natural language generation, reasoning, and comprehension. This study aims to construct prompts and comments grounded in the diverse scoring criteria delineated within the official TOEFL guide. The primary objective is to assess the capabilities and constraints of ChatGPT, a prominent representative of large language models, within the context of automated essay scoring. The prevailing methodologies for automated essay scoring involve the utilization of deep neural networks, statistical machine learning techniques, and fine-tuning pre-trained models. However, these techniques face challenges when applied to different contexts or subjects, primarily due to their substantial data requirements and limited adaptability to small sample sizes. In contrast, this study employs ChatGPT to conduct an automated evaluation of English essays, even with a small sample size, employing an experimental approach. The empirical findings indicate that ChatGPT can provide operational functionality for automated essay scoring, although the results exhibit a regression effect. It is imperative to underscore that the effective design and implementation of ChatGPT prompts necessitate a profound domain expertise and technical proficiency, as these prompts are subject to specific threshold criteria. Keywords: ChatGPT, Automated Essay Scoring, Prompt Learning, TOEFL Independent Writing Task