The Well-Being of Chinese EFL Students Within AI-Based Context: Exploring the Role of Personality Traits and Psychological Capital

IF 5.3 3区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Zhen Guo
{"title":"The Well-Being of Chinese EFL Students Within AI-Based Context: Exploring the Role of Personality Traits and Psychological Capital","authors":"Zhen Guo","doi":"10.1111/ejed.70703","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>In the language learning domain, learner psychological well-being has emerged as a critical outcome influenced by different psychological resources. Given that artificial intelligence (AI) has entered language learning at a fast pace, the psychological impact of AI on learners is now more pertinent. Both personality traits and psychological capital have been individually linked to learners' success and well-being, yet their combined influence in technology-based language learning contexts remains underexplored. This study investigates the predictive roles of personality traits and psychological capital in predicting the well-being of English as a Foreign Language (EFL) learners in AI-based environments. Adopting Seligman's PERMA theory, the study conceptualises personality traits (PTs) as stable internal resources and psychological capital (PsyCap) as a state element. A total of 373 EFL university students participated, and they completed the three questionnaires. The Structural equation modelling (SEM) demonstrated that PsyCap (<i>β</i> = 0.713) and PTs (<i>β</i> = 0.642) were both significant predictors of well-being among learners, with PsyCap being the stronger predictor. The study contributes to Positive Psychology (PP) in language learning by establishing a theoretically integrated model of well-being that bridges stable PTs and changeable psychological strengths.</p>\n </div>","PeriodicalId":47585,"journal":{"name":"European Journal of Education","volume":"61 3","pages":""},"PeriodicalIF":5.3000,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Education","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ejed.70703","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

Abstract

In the language learning domain, learner psychological well-being has emerged as a critical outcome influenced by different psychological resources. Given that artificial intelligence (AI) has entered language learning at a fast pace, the psychological impact of AI on learners is now more pertinent. Both personality traits and psychological capital have been individually linked to learners' success and well-being, yet their combined influence in technology-based language learning contexts remains underexplored. This study investigates the predictive roles of personality traits and psychological capital in predicting the well-being of English as a Foreign Language (EFL) learners in AI-based environments. Adopting Seligman's PERMA theory, the study conceptualises personality traits (PTs) as stable internal resources and psychological capital (PsyCap) as a state element. A total of 373 EFL university students participated, and they completed the three questionnaires. The Structural equation modelling (SEM) demonstrated that PsyCap (β = 0.713) and PTs (β = 0.642) were both significant predictors of well-being among learners, with PsyCap being the stronger predictor. The study contributes to Positive Psychology (PP) in language learning by establishing a theoretically integrated model of well-being that bridges stable PTs and changeable psychological strengths.

人工智能背景下中国英语学生的幸福感:人格特质和心理资本的作用探讨
在语言学习领域,学习者的心理健康已成为受不同心理资源影响的重要结果。鉴于人工智能(AI)已经快速进入语言学习领域,人工智能对学习者的心理影响现在更加相关。人格特质和心理资本都与学习者的成功和幸福有关,但它们在基于技术的语言学习环境中的综合影响仍未得到充分探讨。本研究探讨了人格特质和心理资本对人工智能环境下英语学习者幸福感的预测作用。本研究采用Seligman的PERMA理论,将人格特质(PTs)定义为稳定的内部资源,将心理资本(PsyCap)定义为状态要素。共有373名大学生参与,他们完成了三份问卷。结构方程模型(SEM)表明,心理cap (β = 0.713)和PTs (β = 0.642)都是学习者幸福感的显著预测因子,其中心理cap的预测作用更强。本研究通过建立一个连接稳定的幸福感和可变的心理优势的理论整合模型,为积极心理学在语言学习中的应用做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
European Journal of Education
European Journal of Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
4.50
自引率
0.00%
发文量
47
期刊介绍: The prime aims of the European Journal of Education are: - To examine, compare and assess education policies, trends, reforms and programmes of European countries in an international perspective - To disseminate policy debates and research results to a wide audience of academics, researchers, practitioners and students of education sciences - To contribute to the policy debate at the national and European level by providing European administrators and policy-makers in international organisations, national and local governments with comparative and up-to-date material centred on specific themes of common interest.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书