European Journal of Education最新文献

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.

This article critically examines Japan's integration of Generative AI (GenAI) into education by analysing national and local policy frameworks alongside the cultural, ethical and philosophical traditions that shape Japanese views of technology and schooling. The analysis highlights the limitations of AI-driven digital acculturation in the Japanese educational context. It identifies major cultural misalignments between approaches to integrating AI in education (AIED) and the values underpinning the Japanese schooling system across three dimensions: the relational and interdependent self (‘jiko’) versus individualised AI learning pathways; the selfless teacher ideal (‘kenshin-teki kyōshi-zō’) challenged by new professional pressures; and community-based school practices (‘tokubetsu katsudō’) that cannot be authentically replicated through digital technologies. While Japan's Society 5.0 vision promotes human-centred innovation grounded in dignity, diversity and sustainability, AI policy often reflects neoliberal values emphasising efficiency and individualism. The findings suggest that integrating AI harmoniously into Japanese educational culture requires the promotion of interdependent learning, the balanced role of teachers and enhancement in community-forming aspects of education.

In the era of digital transformation, Artificial Intelligence (AI) has emerged as a transformative force in higher education, reshaping how students learn, interact, and prepare for the world of work. This study examined the influence of AI usage on the multidimensional construct of graduate capital (GC) among higher education students in Ghana. Adopting a descriptive survey design, data were collected from 635 students who had prior experience with AI technologies in their academic activities. A purposive sampling technique was used to ensure that participants had meaningful engagement with AI tools. The study employed Partial Least Squares Structural Equation Modelling (PLS-SEM) using SmartPLS 4 software to analyse the data. Measurement model assessment confirmed strong reliability and validity across constructs, while the structural model revealed that AI usage had a significant and positive influence on all five dimensions of GC: human, social, cultural, identity, and psychological. These findings suggest that integrating AI into higher education learning environments can enhance students' employability attributes, human capital, and psychological readiness for professional life. The study contributes to the growing discourse on technology-enhanced learning by positioning AI as a catalyst for holistic graduate development and future workforce adaptability. Implications for educational policy and curriculum design are discussed to guide universities in fostering AI-driven graduate competencies.

Changes in higher education began to emerge with the new development of the fourth industrial revolution (4IR) that featured such buzzwords as robots, artificial intelligence, the Internet of Things and blockchain. These paradigm shifts provide new opportunities for sustainability and transparent sharing of knowledge and create new challenges. Therefore, the research investigates the topics of open educational resources, sustainability practices and digital change in higher education. To investigate surveys on research in Germany, Canada and Australia regarding transformations caused by 4IR technologies in sustaining sustainability and availability of knowledge, a comprehensive literature review and bibliometric analysis were established. The 4IR technologies have been found to promote comprehensive and inclusive, sustainable and cheap educational models. Nevertheless, unaddressed concerns regarding infrastructural impediments to implementation, absence of digital care and fragmented policy regimes still hamper the achievement of those benefits. The authors request the complete implementation of sustainability in digital education, and strategic application of OER to knowledge universal access. Institutions that have undertaken the 4IR technologies are recommended to maintain resilience in and of the higher education systems.

Digital technology adoption may not directly boost teachers' ICT-enabled productivity; fostering a supportive school digital culture is crucial. Grounded in the stressor-strain-outcome model and job demands-resources theory, this study addresses this pressing issue by examining the techno-stressors and emotional exhaustion experienced by 2000 K-12 teachers in China. The results revealed that: (1) school digital culture helped mitigate various techno-stressors; (2) techno-complexity and techno-insecurity were related to increased emotional exhaustion; (3) intriguingly, techno-uncertainty showed a negative association with emotional exhaustion; (4) emotional exhaustion was negatively linked to ICT-enabled productivity. Additionally, group differences by gender and location were unveiled. This study provides a psychological perspective on how technostress influences the relationship between school digital culture and teacher productivity, and offers evidence-based strategies to alleviate teachers' technostress.

Data-driven decision-making has become increasingly important for improving school processes and strengthening instructional and managerial practices. Despite the growing emphasis on data use in education, little is known about how schools and teachers operationalise data in their daily decision-making processes. This study examined the implementation of data-driven decision-making at both the school and classroom levels, as well as the associated challenges. The study involved 12 teachers and 13 school principals in Turkey, selected through snowball sampling, and collected data through semi-structured interviews, analysed using content analysis. The study reveals that school participants struggle with data analysis due to time constraints, lack of data literacy skills, and lack of stakeholder support. The research recommends coordination with senior management units and stakeholder cooperation to acquire necessary knowledge and skills for data use, emphasising the importance of effective data management.