European Journal of Education最新文献

Against the backdrop of intense exam pressure and English curriculum reforms, EFL teachers face persistent occupational strains, yet existing research lacks sufficient insights into the dynamic formation mechanism of teacher resilience. Grounded in the bioecological theory, this study adopted semi-structured interviews with five senior high EFL teachers to unpack the development of teacher resilience. Findings identify four core dimensions of EFL teachers' resilience amid occupational challenges, namely professional, emotional, social, and cultural resilience. Furthermore, proximal processes, personal characteristics, multi-layered ecological contexts, and chronosystem interact synergistically to shape EFL teachers' resilience through reciprocal person-environment transactions. This study expands the theoretical perspective for language teacher resilience research and offers practical implications to facilitate teachers' sustainable professional adaptation and wellbeing.

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.

Zhang, D., L. Wen, and J. G. Wu. 2025. “ Structured or Semi-Structured? The Use of Reflection Journals in Postgraduates' Generative Artificial Intelligence Literacy Development in an L2 Academic Writing Context.” European Journal of Education 60, no. 3: e70189. https://doi.org/10.1111/ejed.70189.

1. In paragraph 4 of Section 4.1.1, the data for Dimension 4 were originally reported as ‘(F(1,37) = 0.082, p = 0.231, partial η² = 0.010)’.

The correct values should be ‘(F(1,37) = 0.357, p = 0.554, partial η² = 0.010)’. This correction does not affect the study's conclusions.

2. In paragraph 3 of Section 4.1.1, the results were originally reported as:

‘MANOVA revealed a significant main effect of time (Pillai's Trace = 0.305, F(4, 71) = 7.8, p < 0.001). However, the main effect of group (Pillai's Trace = 0.108, F(4, 71) = 2.145, p = 0.084) and the Time × Group interaction (Pillai's Trace = 0.044, F(4, 71) = 0.825, p = 0.513) were not significant across the four dimensions.’

The correct results should be:

‘MANOVA revealed a significant main effect of time (Pillai's Trace = 0.533, F(4, 34) = 9.704, p < 0.001). However, the main effect of group (Pillai's Trace = 0.171, F(4, 34) = 1.751, p = 0.162) and the Time × Group interaction (Pillai's Trace = 0.141, F(4, 34) = 1.390, p = 0.258) were not significant across the four dimensions.’ This correction does not affect the study's conclusions.

The authors apologise for the errors.

Academic cheating remains a persistent challenge in education across all levels despite various proposed solutions. This study is the first to investigate the integration of an interdisciplinary assessment approach and peer assessment as proactive strategies to enhance academic integrity in unsupervised digital learning environments. A quasi-experimental study with control and experimental groups was conducted with N = 110 students enrolled in primary teacher education, including a control group (n = 55) and an experimental group (n = 55) over one semester. Academic integrity and cheating-related behaviours were measured across three dimensions. The findings revealed statistically significant differences between the experimental and control groups across all dimensions (all p < 0.001), with large effect sizes (η² > 0.14). In addition, Cohen's d values for all dimensions were ≥ 0.80, indicating substantial educational and practical significance. These findings suggest that the intervention was effective in reducing cheating behaviours and strengthening academic integrity in unsupervised digital learning environments. The study highlights the potential of integrating interdisciplinary assessment and peer assessment into contemporary teaching and assessment practices to promote more responsible learning behaviours.

Artificial intelligence (AI) has increasingly reshaped language learning, yet how learners become engaged in AI-assisted language learning remains insufficiently understood. Drawing on self-regulated learning theory, this study examined the relationships among AI literacy, human-AI trust, metacognitive strategies, critical thinking and engagement. A questionnaire survey was conducted with 768 undergraduate students who had experience with AI-assisted language learning. Data were analyzed using structural equation modelling and fuzzy-set qualitative comparative analysis. The structural equation modelling results showed that AI literacy and human-AI trust were positively associated with both metacognitive strategies and critical thinking, which were further related to learner engagement. The mediation results indicated that metacognitive strategies and critical thinking served as significant linking mechanisms between AI-related antecedents and engagement. The configurational analysis revealed that no single condition was necessary for high engagement, while five sufficient configurations were identified, highlighting multiple pathways to engagement. These findings suggest that engagement in AI-assisted language learning is associated with learners' AI-related readiness, self-regulatory processes and critical evaluation. The study provides theoretical and pedagogical insights into self-regulated AI-supported language learning.

Care experienced young people are at higher risk of poor educational outcomes than other young people, but little is known about the relationship between care experience and attendance at a pupil referral unit (PRU), the most common type of alternative educational provision in Wales. This study explored how the type of care experience that a young person has is related to the likelihood of them attending a PRU or other alternative provision. Education data covering the population of Wales was used to create a cohort of young people who were in their last year of compulsory education (aged 15–16) between 2018/2019 and 2020/2021 (n = 93,012). This was linked to data from social care to identify if these young people had ever been in care or in receipt of other social care services. Descriptive statistics and binary logistic regression models were used to compare the likelihood of being in a PRU according to a young person's care experience. Sub-group models were used to compare the relative impact of care experience on being in a PRU for girls and boys. Findings show that the odds of being in a PRU were over twice as high for those young people who entered care after the age of 11 compared to those who had not been in care once Special Educational Needs and exclusion history were controlled for. The percentage of girls in a PRU who were care experienced was higher than the percentage of boys. These findings highlight the need for staff in PRUs to be aware of the increased likelihood of children's services involvement in planning for young people.

Artificial intelligence (AI) is increasingly being integrated into language education, yet evidence regarding its influence on learners' emotional experiences and oral communication remains limited. This mixed-methods study examined the effects of AI-mediated speaking practice on university EFL learners' oral anxiety, speaking enjoyment, self-perceived oral communication competence and willingness to communicate (WTC). A total of 105 intermediate-level learners participated in an eight-week quasi-experimental intervention in which the experimental group engaged in regular AI-mediated speaking activities, whereas the control group completed conventional self-directed speaking practice. Quantitative data were analysed using descriptive and structural equation modelling techniques, and qualitative insights were obtained through semi-structured interviews with 16 participants. Compared with the control group, learners in the AI-mediated condition reported lower speaking anxiety and higher speaking enjoyment, self-perceived communicative competence and willingness to communicate. The structural model indicated that the relationships among AI-mediated practice, emotional experiences, perceived competence and WTC were consistent with the proposed theoretical framework, while interview findings suggested that learners perceived the AI-supported environment as encouraging repeated practice, greater confidence and communicative engagement. These findings support the potential of conversational AI as a complementary tool for facilitating learners' emotional experiences and perceived communicative readiness in EFL speaking instruction, while highlighting the need for future research using behavioural measures and interaction-equivalent comparison conditions to further examine these effects.

Prior research has extensively documented the negative relationship between Foreign Language Anxiety (FLA) and learning strategies, but how this relationship operates among Chinese English majors across different educational levels remains underexplored. To address this, the present study examines the mediating role of academic buoyancy and the moderating effect of educational level in this relationship. A survey of 1609 undergraduate and postgraduate English majors from Chinese universities was conducted to examine the relationships between FLA and four types of learning strategies: memorization, elaboration, cooperation and control strategies. Additionally, the study investigated the mediating role of academic buoyancy and the moderating role of educational level in these relationships. It was found that FLA was negatively associated with academic buoyancy and all four learning strategies, whereas both academic buoyancy and educational level demonstrated positive associations with these strategies. Academic buoyancy predominantly mediated the relationship between FLA and memorization, and that between FLA and cooperation, while partially mediating the relationship between FLA and elaboration and that between FLA and control strategies. Furthermore, educational level significantly moderated the effect of FLA on elaboration specifically. These findings highlight the value of attending to positive emotions in language education and reveal how educational level shapes strategy use. The study offers general implications for language teaching and learning, suggesting that educators should foster students' academic buoyancy and provide differentiated instructional support across degree levels to alleviate anxiety and promote effective strategy employment.

Teacher well-being in challenging educational contexts has important implications for sustainable professional learning, yet less is known about how job demands and job resources operate among EFL teachers in underexamined regional settings. Drawing on Job Demands-Resources theory, this mixed-methods study examined the direct and indirect relationships among job demands, job resources, resilience, teacher efficacy, work engagement and emotional exhaustion among EFL teachers in Western China. A total of 256 valid survey responses were analyzed using Partial Least Squares Structural Equation Modelling, followed by semi-structured interviews with eight teachers to interpret the quantitative patterns. The results showed that job demands significantly predicted emotional exhaustion, but not work engagement. Job resources showed no significant direct effects on either outcome. Instead, both resilience and teacher efficacy mediated the relationships between job demands, job resources and work engagement, whereas only resilience mediated the relationships between job demands, job resources and emotional exhaustion. The interview data further indicated that job demands were experienced as a clear source of fatigue but not necessarily as a reason to disengage from teaching, while resources became effective mainly when they were usable, timely, and connected to concrete problems of practice. The study extends JD-R research by showing how demands and resources helped explain teacher well-being in a challenging EFL context and demonstrating that teacher well-being is closely tied to the conditions under which professional learning can be sustained.

Simulation-based learning is an effective teaching modality. However, there is a lack of evidence regarding scenario-based simulation training with standardized patients on stoma care among nursing students. This study aimed to examine the effect of a scenario-based hybrid simulation training using standardized patients and a wearable bud-shaped stoma on nursing students' knowledge, skills, satisfaction, expectations, and opinions about stoma care. This randomized controlled study included 66 students, 33 in each group. Stoma care was practiced with a standardized patient who had a wearable bud-shaped stoma stuck to the abdomen in the hybrid simulation group and a manikin in the control group. Study data were collected using the Stoma Care Skills Evaluation Form to measure students' skills, a questionnaire to reveal their knowledge and opinions, and the Student Satisfaction and Self-Confidence in Learning Scale to find out about their satisfaction. Students' knowledge and opinion levels in both groups increased statistically significantly following the intervention (p < 0.05). The students in the hybrid simulation group had higher skill (p < 0.001) and satisfaction levels (p = 0.043) than the control group. Scenario-based hybrid simulation training increased students' knowledge, skills, expectations, and opinions about stoma care. It should be considered implementation and dissemination in health education.