European Journal of Education最新文献

Informal groups have a significant impact on organisations. It is seen that the researches in the literature are generally conducted on business organisations and informal groups in educational organisations and approaches to managing these groups are not sufficiently discussed. In this study, the identification of informal groups in schools, teachers' reasons for participating in these groups and administrators' management styles of these groups were examined. The study was conducted with the participation of 345 school administrators and 477 teachers working in the central districts of Ankara. The data were collected with ‘Informal Groups List’, ‘Reasons for Participation in Informal Groups Scale’ and ‘Informal Groups Management Style Scale’. Arithmetic mean, standard deviation, percentage, frequency values were calculated in the analysis of the data; also t-test, Anova and Pearson Correlation Test were applied. According to the results of the study, the most common informal groups in schools are ‘reference groups’, ‘interest groups’, ‘friendship groups’ and ‘benefit groups’. Teachers generally participate in informal groups in order to ‘sense of belonging’, ‘making friends’, ‘being in solidarity’ and ‘share their feelings’. According to administrators' views, administrators manage informal groups in democratic, autocratic and laissez-faire styles, respectively, while according to teachers, administrators adopt democratic, laissez-faire and autocratic management styles, respectively. The findings show that there is a moderate positive relationship between administrators' styles of managing informal groups and teachers' reasons for participating. This study is expected to contribute to the literature by determining the types of informal groups in schools, examining the reasons why teachers participate in these groups, and the management styles of school administrators towards these groups.

This review examines the design and configuration of AI-powered 21st-century classrooms to align with modern pedagogical approaches. The objective was to identify the main characteristics of innovative classroom design through a systematic literature review analysing 90 articles from the Scopus database. The SPAR-4-SRL protocol guided the selection, organisation and assessment of articles, with analysis conducted using descriptive statistics and topic modelling in AtlasTi. Key findings include (a) determinants like acoustics, lighting, temperature, ventilation and dimensions impact learning; (b) flexible furniture arrangements promote collaboration and active learning over traditional row seating; (c) inclusive designs consider sensory needs of students with disabilities; and (d) technology integration is crucial, including smart boards, cameras and connectivity. This comprehensive synthesis highlights some insights into the effect of the use of Artificial Intelligence and the Internet of Things on the architectural principles and environmental factors that optimise classroom spaces for evolving educational practices. Educators, designers and policymakers can apply these insights to create student-centred, technology-enhanced learning environments fostering engagement and inclusivity.

Higher education has witnessed remarkable technological advancements; however, the rapid rise of generative artificial intelligence (Gen AI) presents substantial challenges for teaching and research. This growing reliance has expanded educators' roles, underscoring the need for ethical and selective AI integration while preparing students and researchers for an AI-driven future. Adopting an argumentative perspective, this article analyzes core insights from comparative literature and key reports that highlight Gen AI's potential to diminish critical thinking and negatively impact educational outcomes. Although Gen AI holds transformative promise, its swift expansion raises significant concerns about its long-term implications for education. This research emphasises the need to address Gen AI's drawbacks, advocating for greater awareness and equitable educational practices that support both teaching and learning in academic contexts. Ultimately, the article calls for professional development to equip educators with responsible AI skills, fostering a balanced and ethical approach to Gen AI integration in higher education.

Jaw cyst is a common bone cyst affecting the jaw. Clinically, fenestration decompression is the first choice for treating jaw cysts in children, but traditional strategy still has limitations in positioning accuracy, potential trauma, adherence, etc. This study designed an improved strategy, three-dimensional digital guide plate-based fenestration decompression with sustained plug for the treatment of jaw cyst in an 8-year-old boy. After the surgery, the cyst gradually became smaller and disappeared at 1 year, permanent teeth erupted normally and the wound healed well. Under the positioning of three-dimensional digital guide, the position of fenestration was accurately located, and the anatomical structures in the cyst cavity were protected. The wound was small in size, and the postoperative pain response was mild. Additionally, the expanded structure of the plug at both ends made it firmly fixed in the opening position. The plug could be rinsed daily with simple operation and no pain, avoiding discomfort caused by repeated wearing. To sum up, the improved strategy is effective in the treatment of jaw cyst.

This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model types, frequency, self-study tasks and post-usage feedback. The survey results indicate that ChatGPT is the most frequently used model among ICE undergraduates. Furthermore, we evaluated the performance of GPT-3.5 and GPT-4 on a set of 342 ICE questions sourced from the China MOOC platform. The results reveal significant performance differences between GPT-3.5 and GPT-4 across various ICE sub-disciplines and question types. GPT-4 shows particular proficiency in understanding control technology and system, achieving an accuracy of 82.16%, compared to 68.42% for GPT-3.5. Finally, we explore the factors influencing students use LLMs for ICE self-study and propose strategies for teachers to incorporate LLMs into ICE courses. This study highlights the potential of LLMs to enhance ICE education and provides concrete examples of their application in engineering coursework.

The study delves into the integration of sustainability concepts into management curricula and identifies strategies that business leaders can employ to enhance their environmental consciousness. The study delves deeper into the literature on sustainability education in management curricula, addressing the fundamentals, bringing about significant changes and the tactics to be employed throughout each curriculum phase. The qualitative study is significant. It conducts in-depth interviews with three cohorts of seven respondents each, representing subject facilitators, students and support staff. Interpretative thematic analysis revealed the following themes: management institution infrastructure, preference for sustainability skill sets, job market needs, new hires and philosophical knowledge. The study suggests that the implementation of educational strategies and activities aimed at learning transformation and sustainability knowledge should be coordinated with all the levels of an institute's operations. A provision of a holistic environment that takes into account both micro and macro sustainability aspects is required, and should be meticulously managed, so that the students who will become the managers of tomorrow have the potential to become green business leaders.

The benefits of Generative Artificial Intelligence (GenAI) in enhancing second language (L2) learning are well established. However, these advantages can only be realised if learners are willing to adopt the technology. This study, grounded in the Theory of Planned Behaviour (TPB), investigated the factors influencing the behavioural intention to use GenAI among 337 Chinese college L2 learners using five validated scales. A Structural Equation Modelling (SEM) approach with Amos 24 yielded several key findings. Notably, demographic factors encompassing gender and age did not significantly affect the TPB components. Subjective norm and attitude were found to have a positive and significant impact on behavioural intention, while perceived behavioural control did not demonstrate a significant effect. Furthermore, GenAI literacy emerged as a significant predictor of behavioural intention, both directly and indirectly through its influence on attitude. Collectively, these variables accounted for 51.6% of the variance in behavioural intention. The study also discusses the theoretical and pedagogical implications and offers suggestions for future research.

This study explores the transformative role of AI-enhanced social–emotional learning (SEL) frameworks in improving the engagement and emotional well-being of English as a foreign language (EFL) students in China. A survey was conducted among 816 undergraduate and postgraduate students from universities across five provinces, utilising convenience sampling. The research focused on how AI tools integrated into English learning contribute to student engagement and emotional stability. Data were analysed using SPSS for descriptive and regression analyses and AMOS for structural equation modelling. The findings highlight that AI-enhanced SEL significantly boosts student engagement and emotional well-being. By providing tailored learning experiences based on students' emotional and cognitive needs, AI systems facilitate better emotional regulation, increased focus and improved academic performance. The results suggest that AI-enhanced SEL frameworks offer personalised support that not only enhances learning outcomes but also creates a more emotionally supportive environment, contributing to students' overall academic success and well-being.

While educational environments are swiftly evolving to embrace and offer increased accessibility to technological resources, the inquiry into the appropriate utilisation of Web 2.0 tools in education persists. Thus, this study investigates the efficiency of a blended language learning environment that incorporates Web 2.0 technologies in accordance with a specifically framed instructional design in enhancing English language learning outcomes and social presence. It seeks to explore the impact of incorporating Padlet in English classes on high school students' academic performance and social presence using a mixed-method approach. The standard English test, postinterviews, social presence scale and needs analysis provided the data. Findings indicate that the integration of Padlet into language classes fosters more collaborative language learning settings that result in increased performance in some language skills and social presence. Accordingly, this study is expected to offer valuable insights for educators regarding creating more interactive classroom contexts via Web 2.0 technologies.