Artificial Intelligence‐Supported Student Engagement Research: Text Mining and Systematic Analysis DOI Creative Commons
Xieling Chen, Haoran Xie, S. Joe Qin

и другие.

European Journal of Education, Год журнала: 2025, Номер 60(1)

Опубликована: Янв. 31, 2025

ABSTRACT Artificial intelligence (AI) is increasingly exploited to promote student engagement. This study combined topic modelling, keyword analysis, trend test and systematic analysis methodologies analyse AI‐supported engagement (AIsE) studies regarding research keywords topics, AI roles, systems algorithms, methods domains, samples outcomes. Findings included the following: (1) frequent‐used emerging comprised ‘machine learning’, ‘artificial chatbot’ ‘collaborative knowledge building’. (2) Frequently studied topics ‘AI for MOOCs self‐regulated learning’ ‘affective computing emotional engagement’. (3) Most adopted intelligent tutoring systems, traditional machine learning natural language processing. (4) Emotional affective or psychological states among college students received most attention. (5) quantitative approaches concerned computer science education. Accordingly, we highlighted AI's roles as tutors, advisors, partners, tutees regulators behavioural, cognitive inspire effective integration into

Язык: Английский

Modelling Generative AI Acceptance, Perceived Teachers' Enthusiasm and Self‐Efficacy to English as a Foreign Language Learners' Well‐Being in the Digital Era DOI

Fangwei Huang,

Yongliang Wang, Haijing Zhang

и другие.

European Journal of Education, Год журнала: 2024, Номер unknown

Опубликована: Сен. 28, 2024

ABSTRACT As artificial intelligence (AI) has been integrated into foreign language (FL) education, learners' well‐being is influenced by various factors, including technological, personal and contextual elements. However, few studies explored how external internal factors jointly shape FL in the era of generative AI. To fill this gap, study explores effects AI acceptance, perceived teachers' enthusiasm self‐efficacy on investigating 613 university learners English as a (EFL). The structural equation modelling results reveal that (1) acceptance positively predicts EFL self‐efficacy; (2) does not predict (3) for receptive skills mediates relationship between acceptance/perceived well‐being, whereas productive play mediation role. This research broadens understanding antecedents extends application theory AI‐driven educational environment, providing significant pedagogical implications.

Язык: Английский

Процитировано

43
Engagement and willingness to communicate in the L2 classroom: identifying the latent profiles and their relationships with achievement emotions DOI
Yongliang Wang,

Hanwei Wu,

Yunsong Wang

и другие.

Journal of Multilingual and Multicultural Development, Год журнала: 2024, Номер unknown, С. 1 - 17

Опубликована: Июль 16, 2024

Язык: Английский

Процитировано

32
From Technology‐Challenged Teachers to Empowered Digitalized Citizens: Exploring the Profiles and Antecedents of Teacher AI Literacy in the Chinese EFL Context DOI Open Access
Ziwen Pan, Yongliang Wang

European Journal of Education, Год журнала: 2025, Номер 60(1), С. 1 - 16

Опубликована: Янв. 27, 2025

ABSTRACT Artificial Intelligence (AI) literacy has come to the spotlight, empowering individuals adeptly navigate modern digitalised world. However, studies on teacher AI in English as a Foreign Language (EFL) context remain limited. This study aims identify intraindividual differences and examine its associations with age years of teaching experience among 782 teachers. Given absence reliable instrument measure literacy, we first constructed validated scale encompassing five sub‐scales: Knowledge , Use Assessment Design Ethics . Subsequently, latent profile analysis (LPA) was conducted using Mplus 7.4, results revealing four distinct profiles: Poor (C1: 12.1%), Moderate (C2: 45.5%), Good (C3: 28.4%), Excellent (C4: 14.1%). Multinomial logistic regression analyses indicated significant between both experience. Additionally, 32 respondents participated semi‐structured interviews. The qualitative data analysed MAXQDA 2022 triangulated quantitative offered deeper insights into teachers’ perceptions their literacy. provides theoretical practical implications for understanding Chinese EFL context.

Язык: Английский

Процитировано

3
AI and Uncertain Motivation: Hidden allies that impact EFL argumentative essays using the Toulmin Model DOI Creative Commons
Abdullah Al Fraidan

Acta Psychologica, Год журнала: 2025, Номер 252, С. 104684 - 104684

Опубликована: Янв. 3, 2025

Язык: Английский

Процитировано

2
How AI‐Enhanced Social–Emotional Learning Framework Transforms EFL Students' Engagement and Emotional Well‐Being DOI Open Access

Yue Zong,

Lei Yang

European Journal of Education, Год журнала: 2025, Номер 60(1)

Опубликована: Янв. 12, 2025

ABSTRACT This study explores the transformative role of AI‐enhanced social–emotional learning (SEL) frameworks in improving engagement and emotional well‐being English as a foreign language (EFL) students China. A survey was conducted among 816 undergraduate postgraduate from universities across five provinces, utilising convenience sampling. The research focused on how AI tools integrated into contribute to student stability. Data were analysed using SPSS for descriptive regression analyses AMOS structural equation modelling. findings highlight that SEL significantly boosts well‐being. By providing tailored experiences based students' cognitive needs, systems facilitate better regulation, increased focus improved academic performance. results suggest offer personalised support not only enhances outcomes but also creates more emotionally supportive environment, contributing overall success

Язык: Английский

Процитировано

2
The Mediating Roles of Resilience and Flow in Linking Basic Psychological Needs to Tertiary EFL Learners’ Engagement in the Informal Digital Learning of English: A Mixed-Methods Study DOI Creative Commons
Yang Gao, Xiaochen Wang, Barry Lee Reynolds

и другие.

Behavioral Sciences, Год журнала: 2025, Номер 15(1), С. 85 - 85

Опубликована: Янв. 18, 2025

Resilience and flow are crucial in language education, yet most research focuses on formal learning environments, with limited studies their impact informal settings. This study explores the relationship between basic psychological needs engagement context of digital English (IDLE). Using a mixed-methods design, data were collected from 512 Chinese EFL learners. Structural equation modeling NVivo analysis applied to quantitative qualitative data, respectively. The findings reveal that resilience fully mediates engagement, serving as an adaptability enhancer, persistence promoter, stress buffer, self-efficacy builder, emotional regulation facilitator. Conversely, partially this relationship, though perceived competence does not significantly predict context. Building this, contributes intrinsic motivation driver, positive cycle creator, external pressure mitigator, efficiency enhancer. underscores important role IDLE among university students. By highlighting these mediating roles, provides valuable insights for enhancing effectiveness experiences, contributing broader discourse education age.

Язык: Английский

Процитировано

2
Exploring the Effects of Artificial Intelligence Application on EFL Students' Academic Engagement and Emotional Experiences: A Mixed‐Methods Study DOI
Yumeng Guo, Yongliang Wang

European Journal of Education, Год журнала: 2024, Номер unknown

Опубликована: Окт. 27, 2024

ABSTRACT As artificial intelligence (AI) gains prominence, its integration into second language (L2) /foreign (FL) instruction has become a significant trend. Despite the considerable promise of AI for L2/FL learning, more research is still needed on effects student academic engagement in literature classes and corresponding emotional experiences. This study, therefore, aimed to examine use English as foreign (EFL) learners' engagement, experience was also qualitatively explored. Students were allocated experimental group ( N = 48), who received integrated with AI, control traditional without assistance. Quantitative data collected using an FL scale, supplemented by individual semi‐structured interviews qualitative phase. The results indicated that integrating EFL positive effect students' cognitive, social engagement. Moreover, experiences found be abundant dynamic, exerting influence their study provides valuable insights educators researchers regarding instruction.

Язык: Английский

Процитировано

14
Disclosing the Correlation Between Using ChatGPT and Well‐Being in EFL Learners: Considering the Mediating Role of Emotion Regulation DOI Creative Commons
Afsheen Rezai, Ali Soyoof, Barry Lee Reynolds

и другие.

European Journal of Education, Год журнала: 2024, Номер unknown

Опубликована: Сен. 17, 2024

ABSTRACT Artificial Intelligence (AI)‐driven chatbots, such as ChatGPT, have significantly impacted education, especially for English a Foreign Language (EFL) learners. However, there is paucity of empirical evidence concerning the role chatbots in psycho‐emotional constructs like well‐being and emotion regulation. It important to address this issue because it can further our understanding ways through which using ChatGPT affects EFL This study aimed unpack intersection between well‐being, with focus on mediating regulation context Iran. Using convenience sampling, 492 learners (205 males 287 females) were invited complete validated scales measuring use, The outcomes structural equation modelling revealed strong mediation effect relationship well‐being. Additionally, significant positive correlations found both Besides, was established among results imply that integration into Iranian learning environment be beneficial, considering its

Язык: Английский

Процитировано

11
The Effect of Artificial Intelligence Tools on EFL Learners' Engagement, Enjoyment, and Motivation DOI
Lingjie Yuan, Xiaojuan Liu

Computers in Human Behavior, Год журнала: 2024, Номер 162, С. 108474 - 108474

Опубликована: Окт. 12, 2024

Язык: Английский

Процитировано

11
The Effects of Using AI Tools on Critical Thinking in English Literature Classes Among EFL Learners: An Intervention Study DOI Open Access
Wenxia Liu, Yunsong Wang

European Journal of Education, Год журнала: 2024, Номер 59(4)

Опубликована: Окт. 16, 2024

ABSTRACT Artificial intelligence (AI)‐driven learning has become an irreversible trend in foreign language education. Scholars are increasingly focusing on this field, yet few have examined its impact within English literature classes. To fill gap, we designed 8‐week intervention study with mixed methods and recruited 90 students, 42 the experimental group 48 control group, matched for average age, proficiency gender ratio. Critical thinking levels were measured before after using a standardised assessment tool. In students used AI tools (ChatGPT‐3.5, Bodoudou, SummarizBot, etc.) to generate answer text‐related questions, participate interactive quizzes AI‐assisted debates during classes, while followed traditional without tools. The findings revealed statistically significant improvement critical skills of compared as by pre postintervention assessments ( p < 0.05). This suggests that can effectively enhance abilities not only contributes emerging discourse education but also offers practical implications integrating technologies support enrich experiences EFL potential guide educators policymakers designing AI‐driven educational strategies culturally responsive pedagogically effective.

Язык: Английский

Процитировано

11