# An Empirical Study to Understand How Students Use ChatGPT for Writing Essays

arXiv: https://arxiv.org/abs/2501.10551 · HTML: https://mlsanity.com/paper/2501.10551/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Jan 2025.

## Built on by (most cited first, 4 of 4)

- [Understanding University Students' Use of Generative AI: The Roles of Demographics and Personality Traits](https://mlsanity.com/paper/2505.02863/) (2025)
- [Characterizing Students' LLM Usage Behaviors and Their Association with Learning in Critical Thinking Tasks](https://mlsanity.com/paper/2605.04534/) (2026)
- [The Crutch or the Ceiling? How Different Generations of LLMs Shape EFL Student Writings](https://mlsanity.com/paper/2604.15460/) (2026)
- [Telescope: Improving Zero Shot Detection of LLM Generated Content By Measuring Token Repetition Probability](https://mlsanity.com/paper/2607.04061/) (2026)

## Abstract (arXiv)

As large language models (LLMs) advance and become widespread, students increasingly turn to systems like ChatGPT for assistance with writing tasks. Educators are concerned with students' usage of ChatGPT beyond cheating; using ChatGPT may reduce their critical engagement with writing, hindering students' learning processes. The negative or positive impact of using LLM-powered tools for writing will depend on how students use them; however, how students use ChatGPT remains largely unknown, resulting in a limited understanding of its impact on learning. To better understand how students use these tools, we conducted an online study (n=70) where students were given an essay-writing task using a custom platform we developed to capture the queries they made to ChatGPT. To characterize their ChatGPT usage, we categorized each of the queries students made to ChatGPT. We then analyzed the relationship between ChatGPT usage and a variety of other metrics, including students' self-perception, attitudes towards AI, and the resulting essay itself. We found that factors such as gender, race, and perceived self-efficacy can help predict different AI usage patterns. Additionally, we found that different usage patterns were associated with varying levels of enjoyment and perceived ownership over the essay. The results of this study contribute to discussions about how writing education should incorporate generative AI-powered tools in the classroom.