When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms

Fuente: arXiv
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Main Authors: Myung, Junho, Lim, Hyunseung, Oh, Hana, Jin, Hyoungwook, Kang, Nayeon, Ahn, So-Yeon, Hong, Hwajung, Oh, Alice, Kim, Juho
Format: Preprint
Published: 2025
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author Myung, Junho
Lim, Hyunseung
Oh, Hana
Jin, Hyoungwook
Kang, Nayeon
Ahn, So-Yeon
Hong, Hwajung
Oh, Alice
Kim, Juho
author_facet Myung, Junho
Lim, Hyunseung
Oh, Hana
Jin, Hyoungwook
Kang, Nayeon
Ahn, So-Yeon
Hong, Hwajung
Oh, Alice
Kim, Juho
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2512_05506
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms
Myung, Junho
Lim, Hyunseung
Oh, Hana
Jin, Hyoungwook
Kang, Nayeon
Ahn, So-Yeon
Hong, Hwajung
Oh, Alice
Kim, Juho
Human-Computer Interaction
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.
title When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms
topic Human-Computer Interaction
url https://arxiv.org/abs/2512.05506