European Journal of Education最新文献

The mechanisms through which authoritarian-benevolent leadership influences teacher voice behaviour remain underexplored. To address this gap, this study adopts a social exchange theory framework to examine the mediating roles of teacher self-efficacy and trust in principals. Data were collected from 4023 primary and secondary school teachers in China, and structural equation modelling was conducted to analyse the data. The results showed that authoritarian-benevolent leadership was significantly and positively associated with teachers' promotive voice, prohibitive voice, self-efficacy, and trust in principals. Teachers' self-efficacy and trust in principals were significantly and positively associated with both their promotive voice and prohibitive voice. Moreover, teachers' self-efficacy and trust in principals mediated the relationships between authoritarian-benevolent leadership and both promotive voice and prohibitive voice. This study enhances understanding of how authoritarian-benevolent leadership promotes teacher voice behaviour and offers theoretical foundations and empirical insights for school management practices.

The primary objective of this study is to investigate digital inequality in rural education, with a particular focus on implementing effective strategies aimed at mitigating its effects—specifically through enhancing digital literacy among students and educators. The sample comprised 250 students and 50 teachers from two rural schools in China. Data collection instruments included the Digital Inequality Scale and the Digital Literacy Scale, tailored respectively for students and educators. The analysis revealed a significant reduction in the level of digital inequality among both students and teachers. Notably, students demonstrated marked improvements in educational factors (an increase of 6.20 points) and infrastructural factors (5.98 points). Among teachers, the greatest improvements were likewise observed in infrastructural (6.12 points) and educational (6.05 points) domains. This study contributes empirical evidence to inform the development of educational policies and targeted strategies for narrowing the digital divide in rural schools.

This systematic review examines teachers' roles in delivering instructional practices and support systems that enhance learning opportunities for students with special educational needs (SEN) in inclusive classrooms. It also explores how social-pedagogical support influences the academic progress, emotional well-being and social participation of these learners. Using PRISMA guidelines, empirical studies published from 2014 to 2024 in major databases such as PubMed, Scopus and Web of Science were analysed. Findings show that teachers are central to inclusive education, applying strategies like scaffolding, differentiated instruction, cooperative learning and technology-based support to promote equitable outcomes. Collaboration among educators, specialists and families further strengthens students' adjustment and peer interactions. However, challenges such as limited training, insufficient resources and high student-teacher ratios hinder effective implementation. This review underscores the need for continued capacity building, stronger policies and supportive school cultures. It offers practical guidance to advance research, training and policy toward sustainable, impactful, inclusive education.

This study examines the institutional identity, governance, academic strategies, and societal roles of Catholic universities (CUs) in Central and Eastern Europe (CEE), focusing on Poland, Slovakia, Hungary, and Ukraine. It analyses how CUs balance their Catholic identity with secular higher education standards amidst pressures of globalisation, secularisation, and political change. Drawing on documentary analysis and semi-structured interviews with university leaders, the research highlights the distinctive strategic positioning of CUs, their governance structures tied to Church authorities, and their emphasis on holistic education, research, and community engagement. Despite convergence trends with secular universities, CUs in CEE maintain a unique identity grounded in faith-based values, contributing to societal resilience, particularly in contexts of historical oppression and current crises such as the war in Ukraine.

This study examines how configurations of intellectual capital shape knowledge production in university research teams. Using a dataset of Chinese engineering research teams (2017–2021), we find that intellectual capital affects research productivity and influence in distinct ways. Human capital shows nonlinearity: an optimal mix of core and backbone members is associated with higher output and impact. Structural capital exhibits trade-offs: topic breadth and diversity scale publication quantity, whereas excessive topic proliferation and certain coordination structures can dilute citation-based impact; cohesion among prolific authors tends to reduce output but increase impact. Relational capital also depends on tie type: domestic and international academic collaborations enhance both quantity and FWCI—especially international ties—while non-academic collaborations are linked to lower citation impact, consistent with a visibility gap under citation-based evaluation. The findings advance intellectual capital theory by demonstrating contingent, configurational effects at the team level and offer implications for research team governance and evaluation design in higher education.

The role of artificial intelligence (AI) tools in various aspects of education has been examined in the literature. However, music education has sparsely focused on the interface of AI and students' education. To address the gaps, this study employed a mixed-methods study to figure out Chinese music students' AI familiarity and AI self-efficacy and their actual representations using two questionnaires and a semi-structured interview. A total of 317 students took part in the study in two phases. The results of descriptive statistics revealed a moderate to moderately high level of both AI familiarity and AI self-efficacy among the students. In the qualitative phase, it was found that AI familiarity was represented in the participants' “enhanced academic performance”, “enhanced critical thinking and problem-solving skills”, and “provision of AI-driven content”. Moreover, the students showcased their AI self-efficacy in their “successful task completion”, “taking complex projects”, and “helping others by giving them feedback”. The findings are discussed and implications for theory and practice are provided to encourage educators for an AI-powered music education.

In modern AI-powered educational environments, understanding the relational dynamics between teachers and students is essential to fostering effective learning experiences. This study aims to investigate the relationship between teacher interpersonal behaviours and students' emotional engagement, perceived classroom support, technology acceptance, and behavioural engagement in AI-enhanced classrooms. Using a quantitative, correlational research design, data were collected from 500 secondary school students through validated questionnaires measuring each of the five constructs. Structural equation modelling (SEM) was used to assess the direct and indirect effects among variables. The findings indicate that teacher interpersonal behaviours positively influence emotional engagement and perceived support, which in turn enhance students' acceptance of technology and active behavioural engagement. The findings highlight the need for professional development programs that emphasise interpersonal skill development for teachers operating in AI-mediated learning environments.

Sociological research emphasises that hiper-verticality is not only an educational phenomenon, but also a social fact that affects the production of identities. Students are increasingly viewed as “skills carriers” rather than as individuals in training and A.I. contributions to normalising this shift, rendering the cultural and political choices that underpin it invisible. In this context, AI does not merely support learning, but actively participates in defining what counts as legitimate knowledge. Although hyper-vertical pathways enhanced by AI tend to favour those who already possess high cultural capital, capable of integrating technical skills and overview, while for others they translate into rigid trajectories, difficult to reverse, which limit cognitive and social mobility.

The increasing use of artificial intelligence (AI)-driven platforms such as ChatGPT in language classrooms has intensified debates concerning the evolving relationship between teachers and educational technology. Although prior research has largely examined the affordances and challenges of AI for language learning, limited attention has been paid to whether AI is perceived as replacing or complementing language teachers, particularly from the perspectives of AI-literate teachers. Addressing this gap, the present qualitative study explores how 35 AI-literate pre-service English language teachers (PELTs) conceptualise the role of AI-driven platforms in EFL classrooms. Data were collected through written reflections and multiple rounds of semi-structured focus group interviews and analysed using thematic analysis. The findings indicate that AI-driven platforms are perceived as offering significant pedagogical benefits, including enhanced creativity, immediate feedback and increased instructional variety. However, participants consistently emphasised the indispensable role of teachers in providing emotional support, exercising pedagogical judgement and responding to contextual and learner-specific needs. The study concludes that AI-driven platforms should be regarded as complementary pedagogical tools rather than substitutes for language teachers. These findings have important implications for teacher education and for the pedagogically informed integration of AI technologies in L2 classrooms.