European Journal of Education最新文献

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.

The application of artificial intelligence (AI) in early childhood education has been increasingly used to support preschool children's development. However, research indicates that preschool teachers often have limited awareness and literacy regarding AI, and studies focusing on improving their AI-related knowledge remain insufficient. Therefore, enhancing preschool teachers' understanding of AI and supporting its effective integration into educational practices is critically important. This study aimed to examine the impact of an artificial intelligence education programme on preschool teachers' AI awareness. The study was conducted using a quasi-experimental pre-test–post-test control group design and included a total of 48 preschool teachers, with 24 assigned to the experimental group and 24 to the control group. Teachers in the experimental group participated in artificial intelligence education applications, while no such interventions were implemented in the control group. Data were collected using measurement tools administered before and after the intervention. The findings revealed a statistically significant increase in artificial intelligence literacy among teachers in the experimental group compared to those in the control group. These results suggest that artificial intelligence–based educational interventions are effective in improving preschool teachers' awareness and understanding of AI, and they highlight the importance of incorporating AI education into professional development programmes for early childhood educators.