{"title":"Exploring Chinese Secondary EFL Students' Self-Regulated Learning and Task Engagement in AI-Assisted Classrooms: A Latent Growth Curve Modelling Study","authors":"Liu Shi, Shengji Li, Jingjing Xing","doi":"10.1111/ejed.70241","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The growing integration of artificial intelligence (AI) tools into English as a foreign language (EFL) instruction presents new opportunities for fostering students' self-regulated learning (SRL) and task engagement (TE). While prior research has shown that AI-assisted environments can enhance metacognitive monitoring and learning motivation, longitudinal evidence on how SRL and TE develop in tandem remains limited. To address this void, this study employed a parallel-process latent growth curve modelling (LGCM) approach to investigate the co-developmental trajectories of SRL and TE among 334 Chinese secondary school students enrolled in a semester-long AI-assisted EFL programme. Results indicated modest but significant growth in both SRL and TE, with substantial inter-individual variability. Positive correlations were found between the intercepts and slopes of the two constructs, supporting a dynamic reciprocal relationship. However, cross-domain negative effects suggested potential ceiling constraints among highly self-regulated or highly engaged learners. These findings underscore the importance of designing adaptive AI tools that account for diverse learner profiles and sustain long-term engagement and regulation.</p>\n </div>","PeriodicalId":47585,"journal":{"name":"European Journal of Education","volume":"60 4","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-09-11","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.70241","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
The growing integration of artificial intelligence (AI) tools into English as a foreign language (EFL) instruction presents new opportunities for fostering students' self-regulated learning (SRL) and task engagement (TE). While prior research has shown that AI-assisted environments can enhance metacognitive monitoring and learning motivation, longitudinal evidence on how SRL and TE develop in tandem remains limited. To address this void, this study employed a parallel-process latent growth curve modelling (LGCM) approach to investigate the co-developmental trajectories of SRL and TE among 334 Chinese secondary school students enrolled in a semester-long AI-assisted EFL programme. Results indicated modest but significant growth in both SRL and TE, with substantial inter-individual variability. Positive correlations were found between the intercepts and slopes of the two constructs, supporting a dynamic reciprocal relationship. However, cross-domain negative effects suggested potential ceiling constraints among highly self-regulated or highly engaged learners. These findings underscore the importance of designing adaptive AI tools that account for diverse learner profiles and sustain long-term engagement and regulation.
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.