A LLM-based pedagogical framework for active, inquiry-based and adaptive learning in L2 writing

Traditional L2 writing instruction often struggles to provide personalized, process-oriented feedback and engage student motivation. While generative AI like ChatGPT offers a potential solution, its application lacks a robust pedagogical foundation. This study proposes an innovative framework that integrates ChatGPT into L2 writing through a synthesis of active, inquiry-based, and adaptive learning principles. Within the framework, learners occupy the central position, undergoing the teaching implementation of LLM-based six-step writing instruction process to inquisitively learn, experience the teaching assessment of three-dimensional writing evaluation to actively acquire, and the teaching reflection of the plan for the subsequent writing instruction to adaptively improve. Based on a quasi-experimental study involving 50 sophomores, the framework is proved to be effective, enhancing significantly learners’ writing outcomes and motivation. These findings add to the limited body of research on the utilization of ChatGPT in education, providing valuable implications for research and pedagogical practices in L2 writing.

Authors

Institutions

Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-12-20
DOI
https://doi.org/10.1016/j.caeai.2025.100535
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A LLM-based pedagogical framework for active, inquiry-based and adaptive learning in L2 writing

Yan Yin, Ruonan Wang, Yongbo Cao
Computers and Education Artificial Intelligence
Artificial Intelligence in Healthcare and Education
article

A LLM-based pedagogical framework for active, inquiry-based and adaptive learning in L2 writing

Yan Yin, Ruonan Wang, Yongbo Cao
article en

Abstract

Traditional L2 writing instruction often struggles to provide personalized, process-oriented feedback and engage student motivation. While generative AI like ChatGPT offers a potential solution, its application lacks a robust pedagogical foundation. This study proposes an innovative framework that integrates ChatGPT into L2 writing through a synthesis of active, inquiry-based, and adaptive learning principles. Within the framework, learners occupy the central position, undergoing the teaching implementation of LLM-based six-step writing instruction process to inquisitively learn, experience the teaching assessment of three-dimensional writing evaluation to actively acquire, and the teaching reflection of the plan for the subsequent writing instruction to adaptively improve. Based on a quasi-experimental study involving 50 sophomores, the framework is proved to be effective, enhancing significantly learners’ writing outcomes and motivation. These findings add to the limited body of research on the utilization of ChatGPT in education, providing valuable implications for research and pedagogical practices in L2 writing.

Computers and Education Artificial IntelligenceVol. 10
Hubei University (CN), Wuhan Institute of Technology (CN)
Quality Education
Openalex Percentile: Top 41%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.