European Journal of Education最新文献

Self-efficacy and value are key determinants of English as a foreign language (EFL) learning achievement, yet past studies predominantly focused on the average level of students' self-efficacy and value by using variable-centered approaches. Studies on individual differences in EFL learners' self-efficacy and value are still in their infancy. Thus, a person-centered approach (i.e., latent profile analysis) was adopted to identify profiles of students' self-efficacy and value with 491 Chinese EFL learners. Four profiles emerged: (a) low self-efficacy and value; (b) low self-efficacy but medium value; (c) medium self-efficacy and value; and (d) high self-efficacy and value EFL learners. Findings indicated that support from peers emerged as the strongest factor associated with the profile memberships. Moreover, the high self-efficacy and value learners had the highest engagement and academic achievement in learning English. Theoretically, the study extended the Situated Expectancy-Value Theory to the EFL context. Practically, the study underscores the significance of self-efficacy for Chinese EFL learners and recommends placing a stronger emphasis on peer support.

This study aimed to explore preschool teachers' knowledge, attitudes and practices regarding early childhood education for sustainability within the framework of sustainability literacy. To achieve this, we validated the Sustainability Literacy Survey, combining three sections: the Sustainable Development Knowledge Scale, the Attitude toward Sustainable Development Scale and the Early Childhood Education for Sustainability Practices Scale. The survey assesses teachers' understanding of sustainability concepts, their willingness to incorporate sustainability into their teaching, and how they implement sustainability-related practices in their classrooms. We collected data from 345 teachers serving at public and private preschools in Türkiye. Participants varied in teaching experiences and educational backgrounds. Analyses began with exploratory and confirmatory factor analyses to establish the validity and reliability of the three scales. Then, we conducted correlation and regression analyses to examine the relationships among knowledge, attitudes and practices, while t-tests identified differences based on external factors such as school type. The results indicated that education for sustainability practices is primarily driven by teachers' knowledge and attitudes rather than their education level. Although in-service and preservice programs correlated sustainability-related understanding, this knowledge did not directly predict classroom practices. Instead, positive attitudes emerged as the critical factor linking knowledge to sustainability practices.

The present study investigates how EFL teachers' interpersonal behaviours (TIB)—autonomy support, structure (competence support), and involvement (relatedness support)—predict students' behavioural, cognitive, and emotional engagement in generative artificial intelligence (GenAI)-mediated classrooms through the lens of Self Determination Theory (SDT). Survey data from 385 Chinese undergraduates were analysed using partial least squares structural equation modelling (PLS-SEM). Results demonstrate that autonomy support and involvement consistently predict behavioural, cognitive, and emotional engagement, while structure primarily predicts behavioural and cognitive domains. With the structural model explaining 45% of the variance in engagement (R² ≈ 0.45), the findings reaffirm that the motivational climate fostered by teachers remains indispensable despite the affordances of GenAI tools. This study extends SDT-based research by revealing that teacher support mechanisms are recalibrated, not replaced, in GenAI-enhanced classrooms, and highlights the enduring importance of human relational dynamics alongside technological innovation. The results emphasise the need for professional development that integrates GenAI literacy with interpersonal skills to help teachers sustain engagement and optimise learning in evolving educational environments.

Guided by the Valence-Arousal-Dominance (VAD) framework, this study examined how AI-generated voice features in instructional videos influence secondary school students' engagement intentions, mediated by emotional self-dominance (a learner's perceived control over their emotional states). A total of 340 Chinese Grade 8–9 students engaged in mathematical problem-solving tasks while viewing videos that systematically manipulated three voice features: gender (male/female), pitch (low/medium/high) and prosodic prominence (present/absent of emphasising key information). Structural equation modelling revealed significant direct effects of high pitch and prominence on positive engagement intentions toward video-based instruction. Furthermore, self-dominance significantly mediated the relationship between gendered voices and learners' engagement intention levels, with female voices indirectly enhancing student engagement. These findings enhance our understanding of how voice features shape learners' emotional self-dominance and engagement intentions, providing practical guidance for designing instructional multimedia resources in AI-powered educational systems.

Research yields inconsistent findings regarding predictors of teacher self-efficacy (TSE) in inclusive education (IE). Following Bandura's theory, this cross-sectional study analysed predictors of TSE in IE among 3013 teachers from Czech preschool, primary, and secondary schools, where such research is absent. TSE was measured using the Czech-validated Teacher Efficacy for Inclusive Practices scale. Regression analysis tested associations between TSE and gender, school type, and teachers' professional characteristics (length of teaching experience, special education qualifications, support staff experience, perceived IE readiness—retrospective evaluation of how Czech post-IE-reform experience contributed to readiness), including school type interactions. Results revealed descending TSE levels from preschool through secondary schools. Perceived IE readiness was the strongest predictor, particularly for secondary teachers. Special education qualifications were associated with TSE in primary schools, while length of teaching experience showed positive associations across school types. Gender and support staff experience were nonsignificant. Interactions highlight school type-specific professional development needs.