The Impact of GenAI ‐Integrated Instruction on EFL Learners’ Willingness to Communicate, Motivation, and Well‐Being in Tertiary Education: A Mixed‐Effects Modelling Approach

ABSTRACT Willingness to communicate (WTC) is recognised as a vital element in English as a Foreign Language (EFL) learning; however, developing students' WTC in tertiary education is usually a constant challenge. Likewise, improving students' well‐being and motivation is equally significant as these constructs support better engagement and successful language achievement among undergraduate students. Despite the quick incorporation of Generative Artificial Intelligence (GenAI) in education, there remains a critical research gap concerning the effect of GenAI‐supported instruction on the intersection of learners' well‐being, motivational states, and communicative behaviours. Based on Self‐determination Theory (SDT), which underscores the significance of meeting students' primary psychological needs, the current research investigates the way GenAI‐based teaching can affect EFL students' well‐being, motivation, and WTC. The participants were 78 Chinese EFL learners who were assigned to either an experimental group (EXPG) that received GenAI‐supported instruction through ChatGPT or a control group (CG) that received conventional instruction. Three assessment points were used to collect data, namely, a pre‐test, an instant post‐test given at the final stage of intervention, and a delayed post‐test done after 10 weeks. Using Mixed‐Effects Modelling (MEM), the data were analysed to investigate variations over time and variations between groups. The strongest effect was observed for WTC ( d = 1.89), followed by motivation ( d = 1.34) and well‐being ( d = 1.16). The results indicated a significant enhancement in well‐being, motivation, and WTC among students within the EXPG in comparison to those within the CG. By offering empirical evidence of its effect on students' emotional, motivational, and communicative experiences in class settings, the present research can contribute to the increasing body of studies on the usage of GenAI in teaching.

Authors

Institutions

Publication Details

Journal
European Journal of Education
Published
2026-09-10
DOI
https://doi.org/10.1111/ejed.70849
Primary Topic
Motivation and Self-Concept in Sports
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Impact of GenAI ‐Integrated Instruction on EFL Learners’ Willingness to Communicate, Motivation, and Well‐Being in Tertiary Education: A Mixed‐Effects Modelling Approach

Jia Li, Yan Mao, Haiyan Wu
European Journal of Education
Motivation and Self-Concept in Sports
article

The Impact of GenAI ‐Integrated Instruction on EFL Learners’ Willingness to Communicate, Motivation, and Well‐Being in Tertiary Education: A Mixed‐Effects Modelling Approach

Jia Li, Yan Mao, Haiyan Wu
article en

Abstract

ABSTRACT Willingness to communicate (WTC) is recognised as a vital element in English as a Foreign Language (EFL) learning; however, developing students' WTC in tertiary education is usually a constant challenge. Likewise, improving students' well‐being and motivation is equally significant as these constructs support better engagement and successful language achievement among undergraduate students. Despite the quick incorporation of Generative Artificial Intelligence (GenAI) in education, there remains a critical research gap concerning the effect of GenAI‐supported instruction on the intersection of learners' well‐being, motivational states, and communicative behaviours. Based on Self‐determination Theory (SDT), which underscores the significance of meeting students' primary psychological needs, the current research investigates the way GenAI‐based teaching can affect EFL students' well‐being, motivation, and WTC. The participants were 78 Chinese EFL learners who were assigned to either an experimental group (EXPG) that received GenAI‐supported instruction through ChatGPT or a control group (CG) that received conventional instruction. Three assessment points were used to collect data, namely, a pre‐test, an instant post‐test given at the final stage of intervention, and a delayed post‐test done after 10 weeks. Using Mixed‐Effects Modelling (MEM), the data were analysed to investigate variations over time and variations between groups. The strongest effect was observed for WTC ( d = 1.89), followed by motivation ( d = 1.34) and well‐being ( d = 1.16). The results indicated a significant enhancement in well‐being, motivation, and WTC among students within the EXPG in comparison to those within the CG. By offering empirical evidence of its effect on students' emotional, motivational, and communicative experiences in class settings, the present research can contribute to the increasing body of studies on the usage of GenAI in teaching.

European Journal of EducationVol. 61(4)
Inner Mongolia Normal University (CN), East China Normal University (CN)
Quality Education
Openalex Percentile: Top 6%
Motivation and Self-Concept in Sports
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.