European Journal of Education最新文献

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.

This study aims to determine the e-learning readiness of Turkish family physicians and to obtain the views of program instructors to design the e-learning system. An online questionnaire was applied, and 1172 family physicians answered, and a semi-structured interview was done with the program educators. Infrastructure and equipment readiness was 77.64%, and there was a need for quantitative and qualitative improvements. Online learning readiness was 75.13%, and efforts were needed to develop education and online culture. Information technology readiness was 74.47%, and there was a need to develop information technology knowledge. Attitude readiness was 64.22%, and it was insufficient; it was understood that behaviour and desire need to be developed more to improve. Considering demographic characteristics, age was the strongest and most significant predictor of e-learning readiness. In the interviews with the program trainers, e-learning training, development of human resources capacity, increasing enthusiasm for technology, use of asynchronous course format, and development of online culture were indicated for improving an e-learning system for trainers. It was concluded that information technology readiness moderately affected online learning and attitude readiness but slightly affected equipment and infrastructure readiness. As a result, it showed that 72.80% of Turkish family physicians were ready for e-learning and needed several improvements for sufficient e-learning readiness.

As artificial intelligence (AI) technology continues to advance, its influences across various industries have grown, leading to increasing levels of anxiety, including that in education. Nonetheless, in terms of current knowledge, the literature lacks a valid scale to measure AI anxiety among EFL teachers, particularly university EFL teachers. Moreover, the underlying dimensions of this construct have yet to be clarified. Against these gaps, this study aims to develop and validate a scale to assess AI anxiety among university EFL teachers in China. We used qualitative interviews and quantitative surveys combined to identify the key dimensions of AI anxiety of university EFL teachers. In so doing, 251 Chinese EFL teachers completed a newly designed scale. The result of exploratory factor analyses indicated five dimensions and 21 items in the questionnaire. Five dimensions were identified: technical proficiency, job displacement, technological support, student experience and research development. Next, another 415 Chinese EFL teachers participated in validating the scale. The result of confirmatory factor analysis indicated that the scale demonstrated strong reliability, validity and an acceptable model fit. This new scale provides a useful tool for assessing AI anxiety in EFL teachers and highlights the unique challenges they face in adapting to AI, offering a basis for future research and targeted support.