When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, 2026 (CHI 2026)🏆 Best Paper
Abstract
Large language models (LLMs) are promising tools for scaffolding students’ English writing skills, but their effectiveness in real-time K-12 classrooms remains underexplored. Addressing this gap, our study examines the benefits and limitations of using LLMs as real-time learning support, considering how classroom constraints, such as diverse proficiency levels and limited time, affect their effectiveness. We conducted a deployment study with 157 eighth-grade students in a South Korean middle school English class over six weeks. Our findings reveal that while scaffolding improved students’ ability to compose grammatically correct sentences, this step-by-step approach demotivated lower-proficiency students and increased their system reliance. We also observed challenges to classroom dynamics, where extroverted students often dominated the teacher’s attention, and the system’s assistance made it difficult for teachers to identify struggling students. Based on these findings, we discuss design guidelines for integrating LLMs into real-time writing classes as inclusive educational tools.
BibTeX
@inproceedings{10.1145/3772318.3791517,
author = {Myung, Junho and Lim, Hyunseung and Oh, Hana and Jin, Hyoungwook and Kang, Nayeon and Ahn, So-Yeon and Hong, Hwajung and Oh, Alice and Kim, Juho},
title = {When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms},
year = {2026},
isbn = {9798400722783},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3772318.3791517},
doi = {10.1145/3772318.3791517},
abstract = {Large language models (LLMs) are promising tools for scaffolding students’ English writing skills, but their effectiveness in real-time K-12 classrooms remains underexplored. Addressing this gap, our study examines the benefits and limitations of using LLMs as real-time learning support, considering how classroom constraints, such as diverse proficiency levels and limited time, affect their effectiveness. We conducted a deployment study with 157 eighth-grade students in a South Korean middle school English class over six weeks. Our findings reveal that while scaffolding improved students’ ability to compose grammatically correct sentences, this step-by-step approach demotivated lower-proficiency students and increased their system reliance. We also observed challenges to classroom dynamics, where extroverted students often dominated the teacher’s attention, and the system’s assistance made it difficult for teachers to identify struggling students. Based on these findings, we discuss design guidelines for integrating LLMs into real-time writing classes as inclusive educational tools.},
booktitle = {Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems},
articleno = {838},
numpages = {18},
keywords = {Large Language Models (LLMs), Scaffolding, K-12 Education, English as a Foreign Language (EFL), Human-AI Collaboration},
location = {
},
series = {CHI '26}
}