European Journal of Education最新文献

As artificial intelligence (AI) tools become increasingly embedded in education, concerns about their ethical consequences have intensified. Risks such as plagiarism and the potential erosion of students' critical thinking skills underscore the complexity of integrating AI responsibly. Ensuring the ethical use of these technologies is therefore a central challenge for AI in Education (AIED). Yet, how in-service teachers' emotional responses intersect with ethical concerns remains insufficiently understood, despite emotions being pivotal in shaping classroom practice and AI-enabled productivity. Drawing on Appraisal Theory, this case study examines how university English teachers emotionally respond to the ethical principles of AI integration. Thematic analysis of semi-structured interview data revealed distinct emotional patterns associated with different principles of AI ethics. Beneficence was primarily linked to Challenge Emotions and Achievement Emotions, whereas Non-Maleficence, Autonomy, Justice, and Explicability were more often tied to Deterrence Emotions and Loss Emotions. Among these, concerns about Autonomy, particularly student dependence on AI and the erosion of critical thinking, emerged as especially salient. These findings highlight the need for context-sensitive policies, targeted AI training programs, and a stronger emphasis on ethical reflexivity. By showing how teachers' appraisals of ethical principles are closely intertwined with their emotions, the study extends existing research on AI ethics in education and underscores that emotionally informed approaches are indispensable for achieving responsible, sustainable, and human-centered AI integration.

The retention of young teachers in rural schools has been a topic of global concern, and the educational inequality between urban and rural areas has heightened the need for a group of high-quality young teachers to enter rural education. Drawing on Life Course Theory, this paper examines the lived experiences of young teachers in rural China to explore potential strategies for improving their retention in the teaching profession. A total of 10 highly educated young rural teachers were identified through snowball sampling. The results showed that their self-orientation in rural schools was closer to that of a supervisor, accompanied by feelings of isolation at work, low career achievement, deprivation of private time due to work outside teaching, and confusion about future career development. Overall, this paper provides a perspective on rural education from the perspective of young rural teachers and reveals future research trends in rural teacher education.

Epistemic emancipation refers to the erosion of any interference that obstructs subjects' ability to produce, gain and negotiate knowledge. This article argues that epistemic emancipation does not fundamentally and solely proceed from the spatial and temporal presence of alternative epistemologies as an end in itself, nor does it presuppose a complete delinking from the dominant epistemes to reaffirm the originality and non-derivativeness of Southern ways of knowing. This article draws on email interviews with 16 Moroccan university professors, as key agents in unsettling or reproducing epistemic hierarchies, to explore the mobilisations of decoloniality within Moroccan higher education. The findings revealed that (a) Moroccan professors framed epistemic emancipation to be fundamentally about reclaiming intellectual sovereignty from colonial knowledge hierarchies, including paradigms of knowledge production and validation; (b) they mobilised curricular interventions which recenter local epistemes to enact epistemic emancipation, but they were required to navigate institutional constraints; and (c) linguistic hierarchies, colonial institutional policies and epistemological gatekeeping were the main constraints complicating professors' epistemic emancipation struggles.

This sequential explanatory mixed-methods study explored how teachers' autonomy support influences students' learning engagement and well-being in online learning environments, with intrinsic motivation and academic resilience as mediators. Quantitative data were gathered through surveys of 990 university students, followed by in-depth qualitative interviews with 12 selected participants. The quantitative findings revealed that teacher autonomy support positively predicted both learning engagement and well-being. Furthermore, intrinsic motivation and academic resilience mediated the relationship between teacher autonomy support and these outcomes. Interestingly, sequential mediating effects of intrinsic motivation and academic resilience were observed in the association between teacher autonomy support and both learning engagement and well-being. Qualitative analysis identified five key themes: advantages and challenges of online learning, the ideal teacher role, learning motivation, problem-solving strategies, and the overall learning experiences. These findings offer practical insights for enhancing teachers' professional development and designing effective online learning environments.

Research on International Student Mobility (ISM) increasingly examines emerging destinations, reflecting broader dynamics of higher education (HE) internationalisation. The Baltic states—Estonia, Latvia, and Lithuania—offer a compelling example of how small, non-traditional destinations seek to position themselves within global HE markets. This study examines their strategies to enhance attractiveness for international students (IS) and to compete with established Western destinations, using a comparative approach to identify both shared orientations and country-specific practices. All three countries emphasise affordable, high-quality education, labour market relevance, and strategic branding while highlighting unique strengths: Estonia presents itself as a digital innovation hub, Latvia highlights multiculturalism and affordability, and Lithuania foregrounds a blend of educational tradition and modernity. National recruitment strategies operate alongside regional collaboration, collectively enhancing the visibility of the Baltic region internationally. By demonstrating how smaller HE systems leverage affordability, branding, and institutional adaptability, this study contributes to ISM scholarship and offers insights into the ways in which semi-peripheral education systems navigate competition and cooperation within global HE hierarchies.

This study explored how disciplinary culture and instructional medium, specifically English-medium instruction (EMI), influence university students' beliefs about language learning. Using a mixed-methods design, 374 undergraduates from English language teaching (ELT), engineering and medical fields completed the Beliefs About Language Learning Inventory, and 22 students participated in semi-structured interviews. Quantitative analyses revealed significant disciplinary differences across 21 of 34 items and EMI-based differences in 11 items. Qualitative data triangulated these findings. ELT students reported high self-efficacy and intercultural orientation, but stricter views on accuracy. Engineering students reported pragmatic, technology-mediated strategies and instrumental motivation. Medical students showed lower confidence and functional orientations shaped by workload demands. EMI group displayed higher self-efficacy and intercultural engagement. They also exhibited perfectionist views on accuracy and pronunciation. The results show how disciplinary culture and instructional medium shape beliefs in complex and sometimes paradoxical ways. Pedagogical implications are discussed in relation to EMI programs and disciplinary curricula.

This study examines how teacher interpersonal behaviours and AI attributes (responsiveness and anthropomorphism) influence students' willingness to communicate (WTC) with AI through the parallel mediators of classroom enjoyment and AI trust. Using survey data from 557 Chinese undergraduates in AI-enhanced language classrooms, structural equation modelling revealed that teacher–student interaction predicts communication willingness both directly and indirectly through dual mediators. While responsiveness operates fully through indirect pathways, anthropomorphism exerts both direct and indirect effects. Crucially, classroom enjoyment enhances AI trust, confirming a synergistic affective-cognitive sequence. Findings demonstrate teachers' irreplaceable role in AI-enabled classrooms, highlighting human–AI synergy rather than substitution. This dual-mediation perspective offers valuable insights for integrating AI while preserving essential human elements in education. This study examines how teacher interpersonal behaviours and two key AI attributes—responsiveness (speed/fluency of AI feedback) and anthropomorphism (human-like cues of AI)—shape students' willingness to communicate with AI (WTCA) through the parallel mediators of classroom enjoyment and AI trust. Survey data from 557 Chinese undergraduates in AI-enhanced language classrooms were analysed with structural equation modelling. Teacher–student interaction predicted WTCA both directly and indirectly via enjoyment and trust. AI responsiveness operated only through these indirect paths, whereas anthropomorphism exerted additional direct effects. Enjoyment, in turn, enhanced AI trust, confirming an affective-cognitive synergy. Findings underscore teachers' irreplaceable role in human–AI collaborative learning and offer practical guidance for integrating AI without sacrificing essential human elements.

Artificial Intelligence (AI) is reshaping healthcare education, yet structured AI training within physiotherapy programmes remains uneven across the Middle East. We conducted a cross-sectional, multi-country online survey of 3195 undergraduate and internship-level physiotherapy students from nine Middle Eastern countries (Egypt, Jordan, Lebanon, Libya, Palestine, Saudi Arabia, Sudan, Tunisia, and the United Arab Emirates). Using Technology Acceptance Model (TAM) constructs—perceived usefulness (PU) and perceived ease of use (PEOU)—we examined factors associated with AI acceptance and students' perceived barriers to AI integration in physiotherapy education. AI acceptance differed significantly by country (highest in the UAE and lowest in Tunisia), gender (male > female), academic level, GPA, and income (p < 0.05). Prior AI workshop participation, use of specific AI tools (e.g., DeepSeek), perceived time-management benefits, and trust in AI were associated with higher acceptance. In multivariable regression, these sociodemographic and AI-exposure variables explained 24.4% of the variance in AI acceptance. These findings indicate substantial regional disparities in AI preparedness and access, supporting the need for equitable, competency-based AI education and governance policies tailored to physiotherapy training across the Middle East.

The rapid advancement of online learning and artificial intelligence (AI) offers new opportunities to strengthen intellectual property (IP) education, an area still underdeveloped in most educational contexts. This study introduces an AI-driven e-learning system designed to deliver adaptive, differentiated, and globally accessible IP education. By incorporating machine learning, intelligent tutoring, adaptive testing, and gamification, the system creates personalised learning pathways that address diverse learner needs. To evaluate feasibility, synthetic student datasets representing international learners were employed, alongside surveys and interaction logs capturing engagement, satisfaction, usability, and accessibility. Findings reveal that personalization significantly improved engagement, with ratings of 4.3/5 for tailored pathways and 4.5/5 for overall engagement. Multilingual support (4.0) and cultural sensitivity (4.3) were positively perceived, though regional adaptability scored lower (3.2), suggesting a need for localised content. Usability results indicated intuitive navigation and interface design, while technical support emerged as the main area for improvement. Predictive analytics was the most valued AI function (4.2), emphasising its contribution to learner achievement. Overall, the study highlights both theoretical and practical relevance, demonstrating scalable approaches for embedding AI in specialised education to promote inclusivity, global talent development, and cross-cultural collaboration.