# Embracing AI in Education: Understanding the Surge in Large Language Model Use by Secondary Students

arXiv: https://arxiv.org/abs/2411.18708 · HTML: https://mlsanity.com/paper/2411.18708/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 16 references that are in the map.
- First posted on arXiv 27 Nov 2024.

## Builds on (most cited first, 5 of 5)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Mathematical Capabilities of ChatGPT](https://mlsanity.com/paper/2301.13867/) (2023)
- [Large Language Models for Education: A Survey and Outlook](https://mlsanity.com/paper/2403.18105/) (2024)
- [Iris: An AI-Driven Virtual Tutor For Computer Science Education](https://mlsanity.com/paper/2405.08008/) (2024)
- [Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation](https://mlsanity.com/paper/2312.11274/) (2023)

## Built on by (most cited first, 5 of 5)

- [Multilingual Performance Biases of Large Language Models in Education](https://mlsanity.com/paper/2504.17720/) (2025)
- [Confucius3-Math: A Lightweight High-Performance Reasoning LLM for Chinese K-12 Mathematics Learning](https://mlsanity.com/paper/2506.18330/) (2025)
- [A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models](https://mlsanity.com/paper/2504.02793/) (2025)
- [Large Language Models Will Change The Way Children Think About Technology And Impact Every Interaction Paradigm](https://mlsanity.com/paper/2504.13667/) (2025)
- [ELEVATE: Designing Human-Centered GenAI Virtual Tutors for Scalable and Inclusive Education](https://mlsanity.com/paper/2606.30662/) (2026)

## Abstract (arXiv)

The impressive essay writing and problem-solving capabilities of large language models (LLMs) like OpenAI's ChatGPT have opened up new avenues in education. Our goal is to gain insights into the widespread use of LLMs among secondary students to inform their future development. Despite school restrictions, our survey of over 300 middle and high school students revealed that a remarkable 70% of students have utilized LLMs, higher than the usage percentage among young adults, and this percentage remains consistent across 7th to 12th grade. Students also reported using LLMs for multiple subjects, including language arts, history, and math assignments, but expressed mixed thoughts on their effectiveness due to occasional hallucinations in historical contexts and incorrect answers for lack of rigorous reasoning. The survey feedback called for LLMs better adapted for students, and also raised questions to developers and educators on how to help students from underserved communities leverage LLMs' capabilities for equal access to advanced education resources. We propose a few ideas to address such issues, including subject-specific models, personalized learning, and AI classrooms.