Developing and validating a well-being scale for foreign language learners

With the growing emphasis on positive psychology, the well-being of foreign language (FL) learners has become a key area of focus. However, existing well-being scales are typically designed for the general population, and a scale specifically tailored to the unique experiences and challenges faced by FL learners is still lacking. To address this gap, the present study aimed to develop and validate a well-being scale specifically tailored for FL learners. Using a mixed-methods design, the study involved 1,182 secondary school students in China, with an average age of 14.14 years ( SD = 1.21) and spanning grades 7–12. Grounded in the positive emotion, engagement, relationships, meaning, and accomplishment well-being model, exploratory and confirmatory factor analysis confirmed an 18-item FL learner well-being scale. This five-factor scale, including FL positive emotion, FL engagement, FL interpersonal support, FL learning value, and FL accomplishment, demonstrated robust psychometric properties with high internal consistency and split-half reliability, as well as strong convergent, discriminant, and criterion validity. Furthermore, as evidence of criterion-related validity, this study revealed a significant negative correlation between FL learner well-being and FL anxiety, alongside a strong positive association with teacher–student relationships (TSRs). These findings not only provide a reliable tool for assessing FL learner well-being, but also offer empirical support for interventions that aim to enhance student well-being by fostering positive TSRs and reducing FL anxiety.

Authors

Institutions

Publication Details

Journal
Language Teaching Research
Published
2026-02-02
DOI
https://doi.org/10.1177/13621688261416329
Primary Topic
EFL/ESL Teaching and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Developing and validating a well-being scale for foreign language learners

Lihong Ma, Lin Xu, Jiahua Xia
Language Teaching Research
EFL/ESL Teaching and Learning
article

Developing and validating a well-being scale for foreign language learners

Lihong Ma, Lin Xu, Jiahua Xia
article en

Abstract

With the growing emphasis on positive psychology, the well-being of foreign language (FL) learners has become a key area of focus. However, existing well-being scales are typically designed for the general population, and a scale specifically tailored to the unique experiences and challenges faced by FL learners is still lacking. To address this gap, the present study aimed to develop and validate a well-being scale specifically tailored for FL learners. Using a mixed-methods design, the study involved 1,182 secondary school students in China, with an average age of 14.14 years ( SD = 1.21) and spanning grades 7–12. Grounded in the positive emotion, engagement, relationships, meaning, and accomplishment well-being model, exploratory and confirmatory factor analysis confirmed an 18-item FL learner well-being scale. This five-factor scale, including FL positive emotion, FL engagement, FL interpersonal support, FL learning value, and FL accomplishment, demonstrated robust psychometric properties with high internal consistency and split-half reliability, as well as strong convergent, discriminant, and criterion validity. Furthermore, as evidence of criterion-related validity, this study revealed a significant negative correlation between FL learner well-being and FL anxiety, alongside a strong positive association with teacher–student relationships (TSRs). These findings not only provide a reliable tool for assessing FL learner well-being, but also offer empirical support for interventions that aim to enhance student well-being by fostering positive TSRs and reducing FL anxiety.

Language Teaching Research
Ministry of Industry and Information Technology (CN), University of Science and Technology Beijing (CN)
Reduced inequalities
Openalex Percentile: Top 71%
EFL/ESL Teaching and Learning
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.

Developing and validating a well-being scale for foreign language learners — Lihong Ma, Lin Xu, et al. · Language Teaching Research (2026) | TGRS Research Map | TGRS